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Microenvironmental Variables Must Influence Intrinsic Phenotypic Parameters of Cancer Stem Cells to Affect Tumourigenicity

Overview of attention for article published in PLoS Computational Biology, January 2014
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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2 blogs
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62 X users

Citations

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41 Dimensions

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64 Mendeley
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2 CiteULike
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Title
Microenvironmental Variables Must Influence Intrinsic Phenotypic Parameters of Cancer Stem Cells to Affect Tumourigenicity
Published in
PLoS Computational Biology, January 2014
DOI 10.1371/journal.pcbi.1003433
Pubmed ID
Authors

Jacob G. Scott, Anita B. Hjelmeland, Prakash Chinnaiyan, Alexander R. A. Anderson, David Basanta

Abstract

Since the discovery of tumour initiating cells (TICs) in solid tumours, studies focussing on their role in cancer initiation and progression have abounded. The biological interrogation of these cells continues to yield volumes of information on their pro-tumourigenic behaviour, but actionable generalised conclusions have been scarce. Further, new information suggesting a dependence of tumour composition and growth on the microenvironment has yet to be studied theoretically. To address this point, we created a hybrid, discrete/continuous computational cellular automaton model of a generalised stem-cell driven tissue with a simple microenvironment. Using the model we explored the phenotypic traits inherent to the tumour initiating cells and the effect of the microenvironment on tissue growth. We identify the regions in phenotype parameter space where TICs are able to cause a disruption in homeostasis, leading to tissue overgrowth and tumour maintenance. As our parameters and model are non-specific, they could apply to any tissue TIC and do not assume specific genetic mutations. Targeting these phenotypic traits could represent a generalizable therapeutic strategy across cancer types. Further, we find that the microenvironmental variable does not strongly affect the outcomes, suggesting a need for direct feedback from the microenvironment onto stem-cell behaviour in future modelling endeavours.

X Demographics

X Demographics

The data shown below were collected from the profiles of 62 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 5%
India 1 2%
France 1 2%
Ukraine 1 2%
United States 1 2%
Unknown 57 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 28%
Researcher 16 25%
Student > Master 9 14%
Student > Bachelor 6 9%
Student > Doctoral Student 2 3%
Other 5 8%
Unknown 8 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 27%
Biochemistry, Genetics and Molecular Biology 9 14%
Physics and Astronomy 6 9%
Mathematics 5 8%
Computer Science 5 8%
Other 11 17%
Unknown 11 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. 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 25 March 2021.
All research outputs
#927,135
of 25,416,581 outputs
Outputs from PLoS Computational Biology
#701
of 8,977 outputs
Outputs of similar age
#9,963
of 320,098 outputs
Outputs of similar age from PLoS Computational Biology
#8
of 127 outputs
Altmetric has tracked 25,416,581 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,977 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 92% 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 320,098 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.