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accession-icon GSE14900
Transcriptional response of human cells to the absence of mitochondrial DNA
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Mitochondrial biogenesis is under the control of two different genetic systems: the nuclear genome (nDNA) and the mitochondrial genome (mtDNA). mtDNA is a circular genome of 16.6 kb encoding 13 of the approximately 90 subunits that form the respiratory chain, the remaining ones being encoded by the nuclear genome (nDNA). Eukaryotic cells are able to monitor and respond to changes in mitochondrial function through alterations in nuclear gene expression, a phenomenon first defined in yeast and known as retrograde regulation. With this experiment we aimed to identify the set of nuclear genes that significantly change their expression level in response to depletion of mtDNA.

Publication Title

How do human cells react to the absence of mitochondrial DNA?

Sample Metadata Fields

Cell line

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accession-icon GSE4330
Mitochondrial biogenesis induced by PGC-1alpha
  • organism-icon Mus musculus
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Microarray time-course of mouse myotubes transduced with the transcriptional co-activator PGC-1alpha, which is known to induce mitochondrial biogenesis in muscle cells.

Publication Title

Systematic identification of human mitochondrial disease genes through integrative genomics.

Sample Metadata Fields

Cell line

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accession-icon GSE62980
Expression data from mice after knockout or overexpression of Tcfeb in muscle
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcription Factor EB Controls Metabolic Flexibility during Exercise.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE62976
Expression data from Tcfeb KO mice specifically in muscle
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

In order to identify the effects of the absence of Tcfeb on the muscle transcriptome, we performed Affymetrix Gene-Chip hybridization experiments for the KO mice as compared with wt mice

Publication Title

Transcription Factor EB Controls Metabolic Flexibility during Exercise.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP133227
RNA Seq data: A375, A375R, A375DR vorinostat treated, and biopy samples from patients pre- and post- treated with Vorinostat
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

BRAF(V600E) mutant melanomas treated with inhibitors of the BRAF and MEK kinases almost invariably develop resistance, which is frequently caused by reactivation of the Mitogen Activated Protein Kinase (MAPK) pathway. To identify novel treatment options for such patients, we searched for acquired vulnerabilities of MAPK inhibitor-resistant melanomas. We find that resistance to BRAF+MEK inhibitors is associated with increased levels of reactive oxygen species (ROS). Subsequent treatment with the histone deacetylase inhibitor (HDACi) vorinostat represses SLC7A11 that leads to a lethal increase in the already elevated levels of ROS in drug-resistant cells, thereby causing selective apoptotic death of only the drug resistant tumor cells. Consistently, treatment of BRAF inhibitor-resistant melanoma with HDACi in mice results in a dramatic tumor regression. In a study in patients with advanced BRAF+MEK inhibitor resistant melanoma, we find that HDACi can selectively ablate drug-resistant tumor cells, providing clinical proof of concept for the novel therapy identified here. Overall design: one replicate of RNA Seq data A375, A375R, A375DR vorinostat treated and patient samples pre- post- vorinostat treatment

Publication Title

An Acquired Vulnerability of Drug-Resistant Melanoma with Therapeutic Potential.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Cell line, Treatment, Subject

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accession-icon SRP075828
NFIB is a driver of SCLC initiation, progression and metastasis in mouse and marks metastatic disease in patients
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Small Cell Lung Cancer (SCLC) is the most aggressive type of lung cancer with early metastatic dissemination and invariable development of resistant disease for which no effective treatment is available to date. Mouse models of SCLC based on inactivation of Rb1 and Trp53 developed earlier showed frequent amplifications of two transcription factor genes: Nfib and Mycl. Overexpression of Nfib but not Mycl in SCLC mouse results in an enhanced and altered metastatic profile, and appears to be associated with genomic instability. NFIB promotes tumor heterogeneity with the concomitant expansive growth of poorly differentiated, highly proliferative, and invasive tumor cell populations. Consistent with the mouse data, NFIB expression in high-grade human neuroendocrine carcinomas correlates with advanced stage III/IV disease warranting its further assessment as a potentially valuable progression marker in a clinical setting. Overall design: Genomic DNA from mouse small cell lung tumor samples was analyzed by mate pair sequencing and low coverage sequencing. And RNA from Nfib overexpressing mouse small cell lung cancer cell lines was further analyzed for high quality RNA profiles using Illumina Hiseq2500. This series contains only RNA-seq data.

Publication Title

Transcription Factor NFIB Is a Driver of Small Cell Lung Cancer Progression in Mice and Marks Metastatic Disease in Patients.

Sample Metadata Fields

Specimen part, 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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