Evidence map›Paper›PMID 34409594›Full record

ArticleFEBS letters2021

Genome-scale metabolic modelling of SARS-CoV-2 in cancer cells reveals an increased shift to glycolytic energy production.

Elisabeth Yaneske, Guido Zampieri, Loris Bertoldi, Giuseppe Benvenuto, Claudio Angione

Open access · hybridAbstract read
In one paragraph

Article in FEBS letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

14 citing papers in PubMed, 21 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Elisabeth YaneskeSchool of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK.ORCID 0000-0001-6230-4016
Guido ZampieriSchool of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK.ORCID 0000-0002-4518-5913
Loris BertoldiBMR Genomics, Padua, Italy.ORCID 0000-0002-8516-7680
Giuseppe BenvenutoBMR Genomics, Padua, Italy.ORCID 0000-0001-9147-4946
Claudio AngioneSchool of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK.ORCID 0000-0002-3140-7909
Biomolecular Research Genomics (Italy) · ITTeesside University · GBUniversity of Padua · IT

Funding

Children's Liver Disease FoundationUK Research and Innovation
6 · The paper itself

Abstract

Cancer is considered a high-risk condition for severe illness resulting from COVID-19. The interaction between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and human metabolism is key to elucidating the risk posed by COVID-19 for cancer patients and identifying effective treatments, yet it is largely uncharacterised on a mechanistic level. We present a genome-scale map of short-term metabolic alterations triggered by SARS-CoV-2 infection of cancer cells. Through transcriptomic- and proteomic-informed genome-scale metabolic modelling, we characterise the role of RNA and fatty acid biosynthesis in conjunction with a rewiring in energy production pathways and enhanced cytokine secretion. These findings link together complementary aspects of viral invasion of cancer cells, while providing mechanistic insights that can inform the development of treatment strategies.

Indexed as

GlycolysisModels, BiologicalCell Line, TumorCOVID-19Genome, HumanHumansNeoplasmsProteomicsSARS-CoV-2cancerCOVID-19flux balance analysisgenome-scale metabolic modellingmulti-omicsSARS-CoV-2

Identifiers

PMID34409594
PMCPMC8427129
OpenAlexW3194732836

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.