Dataset Information

E-GEOD-57622

ABSTRACT: Gene expression data from mouse hemopoietic stem cells (LSKs), promyelocytes, myelocytes and granulocytes.

OTHER RELATED OMICS DATASETS IN: PRJNA247218PRJNA247242PRJNA247241

PROVIDER: E-GEOD-57622 | ExpressionAtlas | 2015-08-04

REPOSITORIES: ExpressionAtlas

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			Action	DRS
	E-GEOD-57622-analysis-methods.tsv	Tabular
	E-GEOD-57622-atlasExperimentSummary.Rdata	Rdata
	E-GEOD-57622-configuration.xml	Xml
	E-GEOD-57622-percentile-ranks.tsv	Tabular
	E-GEOD-57622.condensed-sdrf.tsv	Tabular

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Project description:Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid derived cells displayed numerous hallmarks of cancer stem cells, which are chemo and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells. To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines. These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines. Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells.

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E-GEOD-57622

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