Evidence map›Paper›PMID 31015463›Full record

ArticleNature communications2019

Metabolic profiling of cancer cells reveals genome-wide crosstalk between transcriptional regulators and metabolism.

Karin Ortmayr, Sébastien Dubuis, Mattia Zampieri

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed
7.1field-weighted citation impact, top 2% 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

72 citing papers in PubMed, 149 citations in OpenAlex.

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12 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Karin OrtmayrInstitute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, CH-8093, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-0603-1073
Sébastien DubuisInstitute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, CH-8093, Zurich, Switzerland.
Mattia ZampieriInstitute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, CH-8093, Zurich, Switzerland. zampieri@imsb.biol.ethz.ch.ORCID http://orcid.org/0000-0002-9339-068X
ETH Zurich · CH

Funding

Austrian Science Fund FWF W 1224
6 · The paper itself

Abstract

Transcriptional reprogramming of cellular metabolism is a hallmark of cancer. However, systematic approaches to study the role of transcriptional regulators (TRs) in mediating cancer metabolic rewiring are missing. Here, we chart a genome-scale map of TR-metabolite associations in human cells using a combined computational-experimental framework for large-scale metabolic profiling of adherent cell lines. By integrating intracellular metabolic profiles of 54 cancer cell lines with transcriptomic and proteomic data, we unraveled a large space of associations between TRs and metabolic pathways. We found a global regulatory signature coordinating glucose- and one-carbon metabolism, suggesting that regulation of carbon metabolism in cancer may be more diverse and flexible than previously appreciated. Here, we demonstrate how this TR-metabolite map can serve as a resource to predict TRs potentially responsible for metabolic transformation in patient-derived tumor samples, opening new opportunities in understanding disease etiology, selecting therapeutic treatments and in designing modulators of cancer-related TRs.

Indexed as

Gene Expression Regulation, NeoplasticCell Line, TumorCell Transformation, NeoplasticGene Expression ProfilingGenome, HumanHumansMetabolic Networks and PathwaysMetabolomeMetabolomicsNeoplasmsProtein Interaction MappingProtein Interaction MapsProteomicsTranscription FactorsTranscriptomeTranscription Factors

Identifiers

PMID31015463
PMCPMC6478870
OpenAlexW2941275129

What Socratic 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 Socratic graph.