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accession-icon SRP101781
Generation of a binary transgenic zebrafish model to study myeloid gene regulation in response to pre-neoplastic melanocytes
  • organism-icon Danio rerio
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

A complex network of inflammation succeeds somatic cell transformation and malignant disease. Immune cells and their associated molecules are responsible for detecting and eliminating cancer cells as they establish themselves as the precursors of a tumour. By the time a patient has a detectable solid tumour, cancer cells have escaped the initial immune response mechanisms. To date, no model exists to allow us to study the underlying mechanisms that govern the initial phase of the immune response as cells are transformed to become the precursors of cancer. Here we describe the development of an innovative double binary animal model designed in zebrafish for exploring regulatory programming of the myeloid cells as they respond to oncogenic transformed melanocytes. This modular system harnesses the power of zebrafish genetics. For studies of melanocyte transformation we generated a hormone-inducible binary system allowing for temporal control of different Ras-oncogene (NRasK61Q, HRasG12V, KRasG12V) expression in melanocytes allowing us to truly study melanoma initiation. This binary model was then coupled to a model for regulatory profiling of the active transcriptome of macrophages and neutrophils which is based on the in vivo biotinylation of nuclei and their subsequent isolation by streptavidin affinity purification. For the first time regulatory profiling of neutrophils as they respond to the earliest precursors of melanoma, revealed a number of factors upregulated in neutrophils that may promote progression to melanoma including fgf1, fgf6, cathepsin H, cathepsin L, galectin 1 and galectin 3. Overall design: We report the design of a double binary approach in zebrafish to study the neutrophil response to transformed melanocytes. By coupling a novel inducible model for melanocyte transformation to a model for the in vivo biotinylation of neutrophil nuclei we can isolate the neutrophil nuclei directly from the in vivo context allowing for RNA-seq analysis of the active transcriptome.

Publication Title

Generation of a double binary transgenic zebrafish model to study myeloid gene regulation in response to oncogene activation in melanocytes.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE75285
mRNA, miRNA and SNP profiles of 50 HB tumors
  • organism-icon Homo sapiens
  • sample-icon 55 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

Genomic analysis of hepatoblastoma identifies distinct molecular and prognostic subgroups.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE75271
mRNA profiles of 50 HB tumors
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hepatoblastoma (HB) is the most common liver cancer in children, but few pre-treatment tumors have been molecularly profiled. Consequently, there are no validated prognostic or therapeutic biomarkers for HB patients. We report on molecular analysis of 88 clinically-annotated HB tumors. This analysis pointed to three risk-stratifying molecular subtypeslow, intermediate and high riskthat are characterized by differential activation of hepatic progenitor cell markers and metabolic pathways. High-risk tumors are characterized by high NFE2L2 activity and LIN28B, HMGA2, SALL4 and AFP expression, low let-7 expression and HNF1A activity, and high coordinated expression of oncofetal proteins and stem cell markers. Tests on a 35 HB validation set supported these genes as prognostic biomarkers.

Publication Title

Genomic analysis of hepatoblastoma identifies distinct molecular and prognostic subgroups.

Sample Metadata Fields

Sex, Specimen part, Race

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accession-icon GSE51822
Expression data for minimally invasive glioblastoma stem-like cell (GSC) plasma membrane markers
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We compared whole genome expression profiles of GSCs with normal human cortex, human neural stem cells (hNSC) from fetal cortex, glioblastoma (GBM) primary, and recurrent tumors to find GSC-specific plasma membrane transcripts.

Publication Title

Myelin-forming cell-specific cadherin-19 is a marker for minimally infiltrative glioblastoma stem-like cells.

Sample Metadata Fields

Cell line

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accession-icon GSE23153
Gene expression in TNF treated rat aortic rings cultured in collagen or fibrin gels.
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

Angiogenesis in cultures of rat aorta begins with neovessels sprouting from the aortic explant within the first three days of culture.

Publication Title

Macrophage-derived tumor necrosis factor-alpha is an early component of the molecular cascade leading to angiogenesis in response to aortic injury.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon GSE23152
Gene expression during first day of collagen gel culture of rat aortic rings
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

Angiogenesis in collagen gel cultures of rat aorta begins with neovessels sprouting from the aortic explant within the first three days of culture.

Publication Title

Macrophage-derived tumor necrosis factor-alpha is an early component of the molecular cascade leading to angiogenesis in response to aortic injury.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP164707
Comparison of the mRNA profile of GDC0032-resistant and GDC0032-sensitive IGROV1 cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The goal was to find pathways which were enriched in the resistant group of cells. Overall design: mRNA profiles of both cell lines were generated by deep sequencing, in triplicate, using Illumina GAIIx.

Publication Title

IGF1R upregulation confers resistance to isoform-specific inhibitors of PI3K in PIK3CA-driven ovarian cancer.

Sample Metadata Fields

Disease, Cell line, Subject

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accession-icon GSE4448
Global analysis of the transcriptional network controlling Xenopus endoderm formation
  • organism-icon Xenopus laevis
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Xenopus laevis Genome Array (xenopuslaevis)

Description

A conserved molecular pathway has emerged controlling endoderm formation in Xenopus zebrafish and mice. Key genes in this pathway include Nodal ligands and transcription factors of the Mix-like paired homeodomain class, Gata4-6 zinc finger factors and Sox17 HMG domain proteins. While a linear epistatic pathway has been proposed, the precise hierarchical relationships between these factors and their downstream targets are largely unresolved. Here we used a combination of microarray analysis and loss-of-function experiments to examine the global regulatory network controlling Xenopus endoderm formation. We identified over 300 transcripts enriched in the gastrula endoderm, including most of the known endoderm regulators as well as over a hundred uncharacterized genes. Surprisingly only 10% of the endoderm transcriptome is regulated as predicted by the current linear model. We find that Nodals, Mixer and Sox17 have both shared and distinct sets of downstream targets and that a number of unexpected autoregulatory loops exist between Sox17 and Gata4-6, Sox17 and Bix1, 2, 4 and between Sox17 and Xnr4. We find that Mixer does not function primarily via Sox17 as previously proposed. This data provides a new insight into the complexity of endoderm formation and will serve as valuable resource for establishing a complete endoderm gene regulatory network.

Publication Title

Global analysis of the transcriptional network controlling Xenopus endoderm formation.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE43798
Microarray of cardiac biventricle from PGC-1a-/-bf/f/MerCre mice
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The following abstract from the submitted manuscript describes the major findings of this work.

Publication Title

A role for peroxisome proliferator-activated receptor γ coactivator-1 in the control of mitochondrial dynamics during postnatal cardiac growth.

Sample Metadata Fields

Specimen part

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accession-icon GSE38654
Genes induced in Xenopus foregut endoderm by mesoderm
  • organism-icon Xenopus laevis
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Xenopus laevis Genome Array (xenopuslaevis)

Description

Foregut organogenesis is regulated by inductive interactions between the endoderm and the adjacent mesoderm. We identified genes induced in the foregut progenitors by the adjacent mesoderm.

Publication Title

Sizzled-tolloid interactions maintain foregut progenitors by regulating fibronectin-dependent BMP signaling.

Sample Metadata Fields

Specimen part

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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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