Table · dataset · 2021
Epithelial-mesenchymal transition status is the main driver of intrinsic metabolism in cancer cell lines
Listed in ETH Zürich Research Collection
A fundamental feature of cancer cells is genomic heterogeneity.
Description
It is a main driver of phenotypic differences, including the response to drugs, and therefore a key factor in therapy selection. Motivated by the increasing role attributed to metabolic reprogramming in tumor development, we wondered how genomic heterogeneity affects metabolic phenotype.
To this end, we profiled the intracellular metabolome of 180 cancer cell lines grown in similar conditions to exclude environmental factors. For each cell line, we estimate activity for 49 pathways across the whole metabolic network. Upon clustering of activity data, we found a convergence into only two major metabolic types.
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These were further characterized by 13C-flux analysis, lipidomics, and analysis of sensitivity to perturbations. These experiments revealed differences in lipid, mitochondrial, and carbohydrate metabolism between the two major types. Finally, a thorough integration of our metabolic data with multiple omics data, revealed a strong association with markers of epithelial-mesenchymal transition (EMT).
Our analysis indicates that in absence of variations imposed by the microenvironment, the metabolism of cancer cell lines falls into only a few major classes despite genetic heterogeneity.
Links
Where it is published
- ETH Zürich Research Collection record hdl.handle.net/20.500.11850/511784 ↗
landing page · from research collection ethz ch
- DOI doi.org/10.3929/ethz-b-000511784 ↗
DOI / persistent id · from research collection ethz ch
Catalogue records · 1
- OAI-PMH record research-collection.ethz.ch/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Awww.… ↗
metadata API · from research collection ethz ch
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Materials Science · Mathematics & Statistics · Medicine & Health · Physics · Psychology & Behavioral Science · Social Science
- Inferred from text
- Cancer 75% · Oncology and carcinogenesis 73%
Provenance · 1 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ETH Zürich Research Collection | oai:www.research-collection.ethz.ch:20.500.11850/511784 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
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| concepts[field].anzsrc:group:3211 | enrichment · research collection ethz ch | taxonomy-embedding@1.0.0 | title+keywords+description (73%) |
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| publication_date | source · research collection ethz ch | connector:research_collection_ethz_ch@1.0.0 | |
| title | source · research collection ethz ch | connector:research_collection_ethz_ch@1.0.0 | /metadata/dc/title |