Evidence map›Paper›PMID 28957320›Full record

ArticlePLoS computational biology2017

A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect.

Chiara Damiani, Riccardo Colombo, Daniela Gaglio, Fabrizia Mastroianni, Dario Pescini, Hans Victor Westerhoff, Giancarlo Mauri, Marco Vanoni, Lilia Alberghina

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

52 citing papers in PubMed, 109 citations in OpenAlex.

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  14. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
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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

9 authors at 3 institutions in 3 countries.

Chiara DamianiSYSBIO Centre of Systems Biology, Milano, Italy.
Riccardo ColomboSYSBIO Centre of Systems Biology, Milano, Italy.
Daniela GaglioSYSBIO Centre of Systems Biology, Milano, Italy.
Fabrizia MastroianniSYSBIO Centre of Systems Biology, Milano, Italy.
Dario PesciniSYSBIO Centre of Systems Biology, Milano, Italy.ORCID http://orcid.org/0000-0002-3090-4823
Hans Victor WesterhoffDept of Molecular Cell Physiology, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands.
Giancarlo MauriSYSBIO Centre of Systems Biology, Milano, Italy.ORCID http://orcid.org/0000-0003-3520-4022
Marco VanoniSYSBIO Centre of Systems Biology, Milano, Italy.
Lilia AlberghinaSYSBIO Centre of Systems Biology, Milano, Italy.
University of Milano-Bicocca · ITInstitute of Molecular Bioimaging and Physiology · ITUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cells share several metabolic traits, including aerobic production of lactate from glucose (Warburg effect), extensive glutamine utilization and impaired mitochondrial electron flow. It is still unclear how these metabolic rearrangements, which may involve different molecular events in different cells, contribute to a selective advantage for cancer cell proliferation. To ascertain which metabolic pathways are used to convert glucose and glutamine to balanced energy and biomass production, we performed systematic constraint-based simulations of a model of human central metabolism. Sampling of the feasible flux space allowed us to obtain a large number of randomly mutated cells simulated at different glutamine and glucose uptake rates. We observed that, in the limited subset of proliferating cells, most displayed fermentation of glucose to lactate in the presence of oxygen. At high utilization rates of glutamine, oxidative utilization of glucose was decreased, while the production of lactate from glutamine was enhanced. This emergent phenotype was observed only when the available carbon exceeded the amount that could be fully oxidized by the available oxygen. Under the latter conditions, standard Flux Balance Analysis indicated that: this metabolic pattern is optimal to maximize biomass and ATP production; it requires the activity of a branched TCA cycle, in which glutamine-dependent reductive carboxylation cooperates to the production of lipids and proteins; it is sustained by a variety of redox-controlled metabolic reactions. In a K-ras transformed cell line we experimentally assessed glutamine-induced metabolic changes. We validated computational results through an extension of Flux Balance Analysis that allows prediction of metabolite variations. Taken together these findings offer new understanding of the logic of the metabolic reprogramming that underlies cancer cell growth.

Indexed as

Cell ProliferationMetabolic Networks and PathwaysModels, BiologicalAnimalsComputer SimulationGlucoseGlutamineHumansLactic AcidMetabolic Flux AnalysisNeoplasmsGlucoseGlutamineLactic Acid

Identifiers

PMID28957320
PMCPMC5634631
OpenAlexW2760505998

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.