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Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

Overview of attention for article published in Frontiers in oncology, January 2013
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Title
Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells
Published in
Frontiers in oncology, January 2013
DOI 10.3389/fonc.2012.00212
Pubmed ID
Authors

Valentina Tosato, Nana-Maria Grüning, Michael Breitenbach, Remigiusz Arnak, Markus Ralser, Carlo V. Bruschi

Abstract

Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants ("translocants"), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Japan 1 1%
Spain 1 1%
Italy 1 1%
Unknown 72 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 25%
Student > Ph. D. Student 17 22%
Student > Doctoral Student 9 12%
Student > Bachelor 6 8%
Student > Master 6 8%
Other 12 16%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 43%
Biochemistry, Genetics and Molecular Biology 23 30%
Medicine and Dentistry 2 3%
Engineering 2 3%
Computer Science 1 1%
Other 5 7%
Unknown 10 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 June 2022.
All research outputs
#15,739,529
of 25,373,627 outputs
Outputs from Frontiers in oncology
#4,962
of 22,416 outputs
Outputs of similar age
#177,354
of 288,991 outputs
Outputs of similar age from Frontiers in oncology
#98
of 328 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 288,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 328 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.