Evidence map›Paper›PMID 36321552›Full record

ArticleMolecular systems biology2022

A functional analysis of 180 cancer cell lines reveals conserved intrinsic metabolic programs.

Sarah Cherkaoui, Stephan Durot, Jenna Bradley, Susan Critchlow, Sebastien Dubuis, Mauro Miguel Masiero, Rebekka Wegmann, Berend Snijder, Alaa Othman, Claus Bendtsen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.3field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 36 citations in OpenAlex.

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  16. Breast cancers as ecosystems: a metabolic perspective.Cellular and molecular life sciences : CMLS · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 4 countries.

Sarah CherkaouiInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0002-0636-4177
Stephan DurotInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0003-2307-7070
Jenna BradleyAstraZeneca, R&D, Cambridge, UK.ORCID 0000-0002-0073-4245
Susan CritchlowAstraZeneca, R&D, Cambridge, UK.ORCID 0000-0002-4647-8988
Sebastien DubuisInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.
Mauro Miguel MasieroInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0002-9632-8144
Rebekka WegmannInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0001-9616-3303
Berend SnijderInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0003-3386-6583
Alaa OthmanInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0002-0092-5594
Claus BendtsenAstraZeneca, R&D, Cambridge, UK.ORCID 0000-0002-8338-987X
Nicola ZamboniInstitute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.ORCID 0000-0003-1271-1021
ETH Zurich · CHAstraZeneca (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cells reprogram their metabolism to support growth and invasion. While previous work has highlighted how single altered reactions and pathways can drive tumorigenesis, it remains unclear how individual changes propagate at the network level and eventually determine global metabolic activity. To characterize the metabolic lifestyle of cancer cells across pathways and genotypes, we profiled the intracellular metabolome of 180 pan-cancer cell lines grown in identical conditions. For each cell line, we estimated activity for 49 pathways spanning the entirety of the metabolic network. Upon clustering, we discovered a convergence into only two major metabolic types. These were functionally confirmed by

Indexed as

MetabolomicsNeoplasmsCell LineHumansMetabolic Networks and PathwaysMetabolomeTumor Microenvironmentcancer metabolismcell linesmetabolic fluxmetabolomicsomics

Identifiers

PMID36321552
PMCPMC9627673
OpenAlexW4308137585

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.