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accession-icon GSE9648
Anticancer metabolites discovered by Computational Metabolomics
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. Nine metabolites predicted to be lowered in Jurkat cells with respect to normal lymphoblasts were examined: riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, -hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole. All, alone or in combination, exhibited antiproliferative activity. Of eleven metabolites predicted to be increased or unchanged in Jurkat cells, only two (bilirubin and androsterone) exhibited significant antiproliferative activity. These results suggest that cancer cell metabolism may be regulated to reduce the intracellular concentration of certain antiproliferative metabolites, resulting in uninhibited cellular growth and have the implication that many other endogenous metabolites with important roles in carcinogenesis are awaiting discovery.

Publication Title

Identification of metabolites with anticancer properties by computational metabolomics.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP049347
Zea mays Transcriptome or Gene expression
  • organism-icon Zea mays
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Endosperm is an absorptive structure that supports embryo development or seedling germination in angiosperms. The endosperm of cereals is a main source of food, feed, and industrial raw materials worldwide. However, the gene regulatory networks that control endosperm cell differentiation remain largely unclear. As a first step toward characterizing these networks, we profiled the mRNAs in five major cell types of the differentiating endosperm and in the embryo and four maternal compartments of the kernel. Comparisons of these mRNA populations revealed the diverged gene expression programs between filial and maternal compartments, and an unexpected close correlation between embryo and the aleurone layer of endosperm. Gene co-expression network analysis identified co-expression modules associated with single or multiple kernel compartments including modules for the endosperm cell types, some of which showed enrichment of previously identified temporally activated and/or imprinted genes. Detailed analyses of a co-expression module highly correlated with the basal endosperm transfer layer (BETL) identified a regulatory module activated by MRP-1, a regulator of BETL differentiation and function. These results provide a high-resolution atlas of gene activity in the compartments of the maize kernel and help to uncover the regulatory modules associated with the differentiation of the major endosperm cell types. Overall design: RNAs from ten compartments of the maize kernel including the central starchy endosperm (CSE), conducting zone (CZ), aleurone (AL), basal endosperm transfer layer (BETL), embryo-surrounding region (ESR), nucellus (NU), pericarp (PE), placenta-chalazal region (PC), the vascular region of the pedicel (PED), and the embryo (EMB) were isolated at 8 days after pollination (DAP) using laser-capture microdissection and sequenced using an Illumina HiSeq 2000 platform.

Publication Title

RNA sequencing of laser-capture microdissected compartments of the maize kernel identifies regulatory modules associated with endosperm cell differentiation.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

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accession-icon GSE66346
Expression data from renal cancer xenograft tumor treated with sunitinib or vehicle
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We established 3 types of primary xenograft models (KURC;Kyoto University Renal Cancer-1,2,3) derived from human renal cell carcinoma tissues, and 40 mg/day of sunitinib was orally administered.

Publication Title

Role of IL13RA2 in Sunitinib Resistance in Clear Cell Renal Cell Carcinoma.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP165834
JunB modulates an IRF4-dependent transcriptional program to regulate homeostasis and suppressive functions of effector regulatory T cells [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

To understand molecular mechanisms by which JunB regulates Treg function, we performed RNA-seq analysis of JunB-deficient and control Treg cells (CD4+ CD25hi). Overall design: Gene expresson profiles in WT and JunB-deficient Treg cells.

Publication Title

JunB regulates homeostasis and suppressive functions of effector regulatory T cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE71627
A common promoter hypomethylation signature in invasive breast, liver and prostate cancer cell lines reveals novel targets involved in cancer invasiveness
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A common promoter hypomethylation signature in invasive breast, liver and prostate cancer cell lines reveals novel targets involved in cancer invasiveness.

Sample Metadata Fields

Sex, Disease, Disease stage, Cell line

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accession-icon GSE71625
A common promoter hypomethylation signature in invasive breast, liver and prostate cancer cell lines reveals novel targets involved in cancer invasiveness (expression)
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Cancer invasion and metastasis is the most morbid aspect of cancer and is governed by different cellular mechanisms than those driving the deregulated growth of tumors. We addressed here the question of whether a common DNA methylation signature of invasion exists in cancer cells from different origins that differentiates invasive from noninvasive cells. We identified a common DNA methylation signature consisting of hyper- and hypomethylation and determined the overlap of differences in DNA methylation with differences in mRNA expression using expression array analyses. A pathway analysis reveals that the hypomethylation signature includes some of the major pathways that were previously implicated in cancer migration and invasion such as TGF beta and ERBB2 triggered pathways. The relevance of these hypomethylation events in human tumors was validated by identification of the signature in several publicly available databases of human tumor transcriptomes. We shortlisted novel invasion promoting candidates and tested the role of four genes from the list C11orf68, G0S2, SHISA2 and TMEM156 in invasiveness using siRNA depletion. Importantly these genes are upregulated in human cancer specimens as determined by immunostaining of human normal and cancer breast, liver and prostate tissue arrays. Since these genes are activated in cancer they constitute a group of targets for specific pharmacological inhibitors of cancer invasiveness.

Publication Title

A common promoter hypomethylation signature in invasive breast, liver and prostate cancer cell lines reveals novel targets involved in cancer invasiveness.

Sample Metadata Fields

Sex, Disease, Disease stage, Cell line

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accession-icon GSE23695
Comparison of Expression profile between CD3-CD56dimCD16+ CD57+ and CD57neg NK cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Thirty to 60% of CD56dimCD16bright NK cells in healthy adults express CD57, which is not expressed on immature CD56bright NK cells or fetal and newborn NK cells. We hypothesized that CD57+ NK cells within the CD56dim mature NK cell subset are highly mature and might be terminally differentiated.

Publication Title

CD57 defines a functionally distinct population of mature NK cells in the human CD56dimCD16+ NK-cell subset.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE134208
Gene expression profiles of mouse embryonic neural stem/progenitor cells during astrocyte differentiation
  • organism-icon Mus musculus
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We performed a microarray experiment to compare gene expression profiles of neural stem/progenitor cells (NS/PCs) with different culture conditions.

Publication Title

Identification of genes associated with the astrocyte-specific gene Gfap during astrocyte differentiation.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE35823
Expression data from Bovine leukemia virus (BLV) Tax-transfected HeLa cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Bovine leukemia virus (BLV) Tax is a transcriptional activator of viral replication and a key contributor to oncogenic potential. We previously identified interesting mutant forms of Tax with elevated (TaxD247G) or reduced (TaxS240P) transactivation effects on BLV replication and propagation. In this study, to identify genes that play a role in the cascade of signal events regulated by wild-type and mutant Tax proteins, we used a large-scale host cell gene-profiling approach.

Publication Title

Identification of bovine leukemia virus tax function associated with host cell transcription, signaling, stress response and immune response pathway by microarray-based gene expression analysis.

Sample Metadata Fields

Cell line

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accession-icon GSE34750
Expression data from Human Tax transfected HeLa cell
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Human T cell leukemia virus type 1 (HTLV-1) Tax is potent activator of viral and cellular gene expression that interacts with a number of cellular proteins. In this study, a large-scale host cell signaling events related to cellular proliferation were used to identify genes involved in Tax-mediated cell signaling events related to cellular proliferation and apoptosis.

Publication Title

Visualizing spatiotemporal dynamics of apoptosis after G1 arrest by human T cell leukemia virus type 1 Tax and insights into gene expression changes using microarray-based gene expression analysis.

Sample Metadata Fields

Cell line

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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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