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accession-icon GSE99860
The effect of GPAM silencing in MCF7 breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

GPAM is well characterized in triglyceride synthesis, but has never been implicated in cancer. Our study report a role for GPAM in cell migration. Gene expression changes after GPAM silencing was investigated to gain insight into possible mechanisms underlying GPAM's role in cell migration.

Publication Title

Glycerol-3-phosphate Acyltransferase 1 Promotes Tumor Cell Migration and Poor Survival in Ovarian Carcinoma.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE99861
The effect of EDI3 inhibition in MCF7 breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

EDI3 was shown to be relevant in cell migration, adhesion and spreading. Gene expression analysis was performed to determine the effect of EDI3 silencing in MCF7 cells in order to gain insight into potential underlying mechanisms.

Publication Title

EDI3 links choline metabolism to integrin expression, cell adhesion and spreading.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE119933
Toxicogenomics directory of rat hepatotoxicants in vivo and in cultivated hepatocytes
  • organism-icon Rattus norvegicus
  • sample-icon 524 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Transcriptomics is developing into an invaluable tool in toxicology. The aim of this study was, using a transcriptomics approach, to identify genes that respond similarly to chemicals (including drugs and industrial compounds) in both rat liver in vivo and in cultivated hepatocytes, which are up- or downregulated by many different test compounds. For this purpose, we analyzed Affymetrix gene array data from 162 compounds that were previously tested in a concentration-dependent manner in rat livers in vivo and rat hepatocytes cultivated in sandwich culture. These data were obtained from the Japanese Toxicogenomics (TGP) and North-Rhine-Westphalian (NRW) data sets, which consist of 138 and 29 compounds, respectively, and have 5 mutual compounds between them. The in vitro gene array data from the NRW data set were generated in the present study, while TGP is publicly available. For each of the data sets, the overlap between up- or down-regulated genes in vitro and in vivo was identified, further named in vitro-in vivo consensus genes. Interestingly, an overlap of in vivo-in vitro consensus genes was obtained between both data sets, which were 21-times (up-regulated genes) or 12-times (down-regulated genes) en-riched compared to random expectation. This is remarkable since the TGP and NRW data sets contained only five mutual compounds. Finally, the genes in the TGP and NRW overlap were used to identify the upregulated genes with the highest com-pound coverage, resulting in a 7-gene set of Cyp1a1, Ugt2b1, Cdkn1a, Mdm2, Aldh1a1, Cyp4a3, and Ehhad. This 7-gene set was then successfully tested with structural analogues of valproic acid that are not present in the TGP and NRW data sets. In conclusion, the 7-gene set identified in the present study responds similarly in vitro and in vivo and is induced by a wide range of different chemicals. Despite these results, transcriptomics with cultivated rat hepatocytes remains a challenge, because many genes are up- or downregulated by the culture conditions, respond differently to test compounds in vitro and in vivo, and shows a higher variability in the in vitro system compared to the corresponding in vivo data.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Disease, Compound

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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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