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accession-icon SRP078248
Adrenalectomy plus corticosterone treatment, rat hippocampal RNA-seq
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Male Sprague-Dawley rats 8 weeks old, were adrenalectomized, treated with 300ug/kg corticosterone or vehicle 3 days after surgery then sacrificed 1 hour later. Hippocampi were removed and RNA extracted and processed for sequencing at the Massachusetts General Hospital Nex-Generation Sequening Core. Overall design: Includes 6 cort treated and 6 control biological replicates

Publication Title

Stress and corticosteroids regulate rat hippocampal mitochondrial DNA gene expression via the glucocorticoid receptor.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE32574
Response of Atf3-/- and WT BMDMs to treatment with LPS for 4 h
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipid-loaded macrophages in the arterial wall. Intimal macrophages internalize modified lipoproteins such as oxidized LDL (oxLDL) through scavenger receptors, leading to storage of excess cholesteryl esters in lipid bodies and a "foam cell" phenotype. In addition, stimulation of macrophage Toll-like receptors (TLRs) has been shown to promote lipid body proliferation. We investigated the possibility that there are transcriptional regulators that are common to both pathways for stimulating foam cell formation (modified lipoproteins and TLR stimulation), and identified the transcription factor ATF3 as a candidate regulator.

Publication Title

ATF3 protects against atherosclerosis by suppressing 25-hydroxycholesterol-induced lipid body formation.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE34219
Effect of integrin alphaV on transcription in 2d or 3d
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

M21 or M21L cells were grown either in a 2-dimensional culture (on plastic) or in a 3-dimensional-collagen model.

Publication Title

Protein kinase Cα (PKCα) regulates p53 localization and melanoma cell survival downstream of integrin αv in three-dimensional collagen and in vivo.

Sample Metadata Fields

Cell line

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accession-icon SRP182110
Oocyte-specific deletion of Mitofusin1 causes female infertility and accelerated follicular depletion
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We performed RNAseq analysis to determine the effect of MFN1 deletion on oocyte global gene expression profile. RNAseq revealed a total of 982 genes were significantly differentially expressed (p<0.05) in Mfn1-/- oocytes compared to WT (654 up-regulated and 337 down-regulated). Pathway analysis indicated significant over-representation of elements involved in regulation of ceramide biosynthesis, death receptor signaling and adherens junction signaling. Differential expression of these genes (Bad, G2e3, Cdh17 and Myh2) was also confirmed by qRT-PCR.Our findings provide new insight into the role of MFN1 in the oocytes, and may help understand the potential mechanism of infertility and reproductive aging associated with MFN1-deficiency. Overall design: Secondary follicle-enclosed oocytes were collected from 8-week-old Mfn1-/- and WT mice (n=3 for each group) and 5 oocytes from each group were pooled for RNA sequencing analysis.

Publication Title

Mitofusin 1 is required for female fertility and to maintain ovarian follicular reserve.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE30183
Expression profiling of MCF7 cells upon nutlin3a treatment
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The tumor suppressor p53 can induce various biological responses. Yet it is not clear whether it is p53 in vivo promoter selectivity that triggers different transcription programs leading to different outcomes. Our analysis of genome-wide chromatin occupancy by p53 using ChIP-seq (deposited in Sequence Read Archive database as SRP007261) revealed p53 default program, i.e. the pattern of major p53-bound sites that is similar upon p53 activation by nutlin3a, RITA or 5-FU in breast cancer cells, despite different biological outcomes triggered by these compounds. Parallel analysis of gene expression allowed identification of 280 previously unknown p53 target genes, including p53-repressed AURKA. The consensus p53 binding motif was present more frequently in p53-induced, than in repressed targets, indicating different mechanisms of gene activation versus repression. We identified several possible cofactors of p53, and found that STAT3 antagonised p53-mediated repression of a subset of genes, including AURKA. Finally, we showed that the expression of the novel p53 targets correlates with p53 status and survival in breast cancer patients.

Publication Title

Insights into p53 transcriptional function via genome-wide chromatin occupancy and gene expression analysis.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE11578
Effect of wtp53-reactivating drug RITA on HCT116 cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Since its discovery as a tumour suppressor some fifteen years ago, the transcription factor p53 has attracted paramount attention for its role as the guardian of the genome. TP53 mutations occur so frequently in cancer, regardless of patient age or tumour type, that they appear to be part of the life history of at least 50% of human tumours. In most tumours that retain wild-type p53, its function is inactivated due to deregulated HDM2, a protein which binds to p53 and which can inhibit the transcriptional activity of p53 and induce its degradation.

Publication Title

Ablation of key oncogenic pathways by RITA-reactivated p53 is required for efficient apoptosis.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE65168
Cellular and molecular characterization of the altered metabolism in RCC
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

RCC cells (786-O) were transfected with VHL. The parental cell line should be compared to the transfectant (+VHL) under nomoxia as well as under hypoxia conditions.

Publication Title

Distinct von Hippel-Lindau gene and hypoxia-regulated alterations in gene and protein expression patterns of renal cell carcinoma and their effects on metabolism.

Sample Metadata Fields

Cell line

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accession-icon GSE13291
MCF7 time-series upon RITA treatment.
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Targeting oncogene addiction is a promising strategy for anti-cancer therapy. Here, we report a potent inhibition of crucial oncogenes by p53 upon reactivation with small molecule RITA in vitro and in vivo. RITA-activated p53 unleashes transcriptional repression of anti-apoptotic proteins Mcl-1, Bcl-2, MAP4, and survivin, blocks Akt pathway on several levels and downregulates c-Myc, cyclin E and B-catenin. p53 ablates c-Myc expression via several mechanisms at transcriptional and posttranscriptional level. We show that transrepression of oncogenes correlated with higher level of p53 bound to chromatin-bound p53 than transactivation of pro-apoptotic targets. Inhibition of oncogenes by p53 reduces the cells ability to buffer pro-apoptotic signals and elicits robust apoptosis. Our study highlights the role of transcriptional repression for p53-mediated tumor suppression.

Publication Title

Ablation of key oncogenic pathways by RITA-reactivated p53 is required for efficient apoptosis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP069768
Senescence-associated lncRNAs: senescence-associated long noncoding RNAs.
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Noncoding RNAs include small transcripts, such as microRNAs and piwi-interacting RNAs, and a wide range of long noncoding RNAs (lncRNAs). Although many lncRNAs have been identified, only a small number of lncRNAs have been characterized functionally. Here, we sought to identify lncRNAs differentially expressed during replicative senescence. We compared lncRNAs expressed in proliferating, early-passage, 'young' human diploid WI-38 fibroblasts [population doubling (PDL) 20] with those expressed in senescent, late-passage, 'old' fibroblasts (PDL 52) by RNA sequencing (RNA-Seq). Numerous transcripts in all lncRNA groups (antisense lncRNAs, pseudogene-encoded lncRNAs, previously described lncRNAs and novel lncRNAs) were validated using reverse transcription (RT) and real-time, quantitative (q)PCR. Among the novel senescence-associated lncRNAs (SAL-RNAs) showing lower abundance in senescent cells, SAL-RNA1 (XLOC_023166) was found to delay senescence, because reducing SAL-RNA1 levels enhanced the appearance of phenotypic traits of senescence, including an enlarged morphology, positive ß-galactosidase activity, and heightened p53 levels. Our results reveal that the expression of known and novel lncRNAs changes with senescence and suggests that SAL-RNAs play direct regulatory roles in this important cellular process. Overall design: RNA was extracted from both young and senescent WI-38 cells and used for total RNA-Seq.

Publication Title

Senescence-associated lncRNAs: senescence-associated long noncoding RNAs.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE29598
A Methodology for Utilization of Predictive Genomic Signatures in FFPE Samples
  • organism-icon Homo sapiens
  • sample-icon 117 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Purpose: Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential. Experimental Design: Patterns of pathway activity in matched fresh-frozen and FFPE xenograft tumor samples were generated using the MessageAmp Premier methodology in combination with assays using Affymetrix arrays. Results generated were compared with those obtained from fresh-frozen samples using a standard Affymetrix assay. In addition, gene expression data from patient matched fresh-frozen and FFPE melanomas were also utilized to evaluate the consistency of predictions of oncogenic signaling pathway status. Results: Significant correlation of pathway activity predictions was observed between paired fresh-frozen and FFPE xenograft tumor samples. In addition, significant concordance of pathway activity predictions was also observed between patient matched fresh-frozen and FFPE melanomas. Conclusion: Reliable and consistent predictions of oncogenic pathway activities can be obtained from FFPE tumor tissue samples. The ability to reliably utilize FFPE patient tumor tissue samples for genomic analyses will lead to a better understanding of the biology of disease progression and, in the clinical setting, will provide tools to guide the choice of therapeutics to those most likely to be effective in treating a patients disease.

Publication Title

A methodology for utilization of predictive genomic signatures in FFPE samples.

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)

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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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