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accession-icon GSE17566
Inactivation of Unr results in induction of differentiation of murine ES cells into the primitive endoderm lineage
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Unr (upstream of N-ras) is a cytoplasmic RNA-binding protein with cold shock domains, involved in regulation of messenger RNA stability and translation. To address the biological role of Unr, we inactivated the unr gene by homologous recombination in mice and embryonic stem (ES) cells. Embryos deficient for Unr die at mid-gestation, and the main phenotypic defects observed, growth deficiency and absence of neural tube closure, suggest a role of Unr in the balance proliferation/differentiation during early development. Here, we report that in Unr-null ES cell cultures, we observed a greater proportion of partially differentiated colonies, together with dispersed, refractile cells with stellate morphology, reminiscent of primitive endoderm (PrE) cells. DNA microarray, immunostaining, and RNA analyses revealed that Unr-null ES cells express a set of PrE markers, including the GATA6 transcription factor, a key inducer of PrE. Although Unr-deficient cells did not downregulate the pluripotency regulators Oct4, Nanog and Sox2, they grew more slowly than the wild-type lines, and their clonogenicity was lower. Silencing of Unr by RNA interference in ES E14 (129 genetic background) resulted in similar phenotypic and molecular changes as those observed in unr-/- ES cells (C57Bl/6 background). Finally, we show that ectopic expression of Unr in unr-/- ES cells partially reverses the endoderm-specific gene expression and the differentiation phenotype.

Publication Title

The RNA-binding protein Unr prevents mouse embryonic stem cells differentiation toward the primitive endoderm lineage.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE11951
Gene expression variation induced by loss of the CD146 mRNA in MDA-MB-231
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Metastasis is a complex process involving loss of adhesion, migration, invasion and proliferation of cancer cells. Cell adhesion molecules play a pivotal role in this phenomenon by regulating cell-cell and cell-matrix interactions. CD146 (MCAM) is associated with advanced tumor stage in melanoma, prostate and ovarian cancers.

Publication Title

CD146 expression is associated with a poor prognosis in human breast tumors and with enhanced motility in breast cancer cell lines.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE111594
Whole-genome transcriptomic analysis of Notch1-expressing cells in mouse intestinal tumours
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

To define and compare the genome-wide transcriptional signatures of Notch1+ cells in intestinal tumors and in normal ISCs we performed Affymetrix analyses of these two populations.

Publication Title

Lineage tracing of Notch1-expressing cells in intestinal tumours reveals a distinct population of cancer stem cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE21653
A gene expression signature identifies two prognostic subgroups of basal breast cancer
  • organism-icon Homo sapiens
  • sample-icon 265 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Medullary breast cancers (MBC) display a basal profile, but a favorable prognosis. We hypothesized that a previously published 368-gene expression signature associated with MBC might serve to define a prognostic classifier in basal cancers. We collected public gene expression and histoclinical data of 2145 invasive early breast adenocarcinomas. We developed a Support Vector Machine (SVM) classifier based on this 368-gene list in a learning set, and tested its predictive performances in an independent validation set. Then, we assessed its prognostic value and that of six prognostic signatures for disease-free survival (DFS) in the remaining 2034 samples. The SVM model accurately classified all MBC samples in the learning and validation sets. A total of 466 cases were basal across other sets. The SVM classifier separated them into two subgroups, subgroup 1 (resembling MBC) and subgroup 2 (not resembling MBC). Subgroup 1 exhibited 71% 5-year DFS, whereas subgroup 2 exhibited 50% (p=9.93E-05). The classifier outperformed the classical prognostic variables in multivariate analysis, conferring lesser risk for relapse in subgroup 1 (HR=0.52, p=3.9E-04). This prognostic value was specific to the basal subtype, in which none of the other prognostic signatures was informative.

Publication Title

A gene expression signature identifies two prognostic subgroups of basal breast cancer.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE45437
Expression data from paediatric ependymoma short-term cell cultures
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Promoter hypermethylation and transcriptional silencing is a common epigenetic mechanism of tumour suppressor inactivation in cancer, including malignant brain tumours.

Publication Title

Epigenetic genome-wide analysis identifies BEX1 as a candidate tumour suppressor gene in paediatric intracranial ependymoma.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE23720
High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes
  • organism-icon Homo sapiens
  • sample-icon 197 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples. Genomic imbalances of 49 IBCs and 124 nIBCs were determined using high-resolution array-comparative genomic hybridization, and mRNA expression profiles of 197 samples using whole-genome microarrays. Genomic profiles of IBCs were as heterogeneous as those of nIBCs, and globally relatively close. However, IBCs showed more frequent complex patterns and a higher percentage of genes with CNAs per sample. The number of altered regions was similar in both types, although some regions were altered more frequently and/or with higher amplitude in IBCs. Many genes were similarly altered in both types; however, more genes displayed recurrent amplifications in IBCs.

Publication Title

High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes.

Sample Metadata Fields

Age

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accession-icon GSE46874
Effects of Combined Persistant Organic Pollutants on Global Gene Expression in Human HepaRG Cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The exposure to and contamination by Persistent Organic Pollutants (POPs), which include pesticides used worldwide and polyaromatic hydrocarbons, is detrimental to human health and diverse ecosystems. Although most mechanistic studies have focused on single compounds, living organisms are exposed to multiple environmental xenobiotics, simultaneously, throughout their lives. The experimental evidence useful for assessing the effects of exposure to pollutant mixtures is scarce. We investigated the effects of exposure to a combination of two POPs, which employ different xenosensors, on global gene expression in a human hepatocyte cell model, HepaRG.

Publication Title

Two persistent organic pollutants which act through different xenosensors (alpha-endosulfan and 2,3,7,8 tetrachlorodibenzo-p-dioxin) interact in a mixture and downregulate multiple genes involved in human hepatocyte lipid and glucose metabolism.

Sample Metadata Fields

Specimen part

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accession-icon GSE35306
Combined hepatocellular-cholangiocarcinomas exhibit progenitor features and activation of Wnt and TGFbeta signaling pathways
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Primary liver tumours include hepatocellular carcinomas (HCC), cholangiocarcinomas (CC) and a group of rare tumours exhibiting biliary and hepatocytic differentiation called combined hepatocholangiocarcinomas (cHCC-CC). To better define this latter group, we take advantage of a series of these tumours based on their morphological characteristics and we performed transcriptional analysis allowing thereafter global comparison with published data. We show that most cHCC-CCs express progenitor cell traits, are committed to biliary lineage and are mainly associated to the activation of Wnt/beta-catenin and TGFbeta signalling pathways. Wnt/beta-catenin pathway activation in cHCC-CC is evidenced by the expression of both its direct targets such as LEF1 and EPCAM. In addition, extracellular matrix (ECM) genes and ECM-remodelling genes which are upon the control of TGF profibrotic program were found up-regulated in cHCC-CC. Interestingly, we show that CC and most cHCC-CC share characteristics associated to a subtype of poorly differentiated HCC suggesting that these tumours could originate from a stem/progenitor cell. The plasticity of these cells may explain the phenotypical heterogeneity of these tumors with the maintenance of some hepatocellular differentiation features such as albumin expression. Interestingly, this is shared by at least one third of CC, raising the hypothesis of a potential continuum between CC, cHCC-CC and poorly differentiated HCC.

Publication Title

Combined hepatocellular-cholangiocarcinomas exhibit progenitor features and activation of Wnt and TGFβ signaling pathways.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE17907
Molecular profiling of ERBB2-amplified breast cancers
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

15-25% of breast cancers (BC) show ERBB2-amplification and overexpression of the encoded ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs may help understand their behavior and design new therapeutic strategies. In this study, we defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. We first identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, we identified 17 genome regions affected by copy number aberration (CNA). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-postive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/-catenin signaling pathway was involved in ER- ERBB2-amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2-amplicon was different in inflammatory (IBC) and non inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. We have shown that ERBB2 BCs are heterogeneous and identified genomic features that may be useful in the design of therapeutical strategies

Publication Title

Genome profiling of ERBB2-amplified breast cancers.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP151817
Genome-wide identification of putative translation regulator cis-Natural Antisense Transcripts in Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 69 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The development of high-throughput genomic technologies has revealed that a large fraction of the genomes of eukaryotes is associated with the expression of noncoding RNAs. One class of noncoding RNA, the cis-natural antisense transcripts (cis-NATs), are particularly interesting as they are at least partially complementary to the protein-coding mRNAs. Although most studies described cis-NATs involved in the regulation of transcription, a few reports have shown recently that cis-NATs can also regulate translation of the cognate sense coding genes in plants and mammals. In order to identify novel examples of translation regulator cis-NATs in Arabidopsis thaliana, we designed a high-throughput experiment based on polysome profiling and RNA-sequencing. Expression of cis-NATs and translation efficiency of the cognate coding mRNAs were measured in roots and shoots in response to various conditions, including phosphate deficiency and treatment with phytohormones. We identified several promising candidates, and validated a few of them experimentally, in Arabidopsis thaliana transgenic lines over-expressing in trans the translation regulator candidate cis-NATs. Overall design: total RNA and polysomal RNA was sequenced from Arabidopsis thaliana whole seedlings grown in high or low pohsphate content, or from roots or shoots from seedlings treated or not with different phytohormones (Ctrl, IAA, ABA,MeJA and ACC). 3 biological replicates were analyzed for each of the 12 experimental conditions.

Publication Title

Prediction of regulatory long intergenic non-coding RNAs acting in trans through base-pairing interactions.

Sample Metadata Fields

Specimen part, Treatment, Subject

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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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