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Impact of Metabolic Heterogeneity on Tumor Growth, Invasion, and Treatment Outcomes

Overview of attention for article published in Cancer Research, April 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
35 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
201 Dimensions

Readers on

mendeley
208 Mendeley
citeulike
2 CiteULike
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Title
Impact of Metabolic Heterogeneity on Tumor Growth, Invasion, and Treatment Outcomes
Published in
Cancer Research, April 2015
DOI 10.1158/0008-5472.can-14-1428
Pubmed ID
Authors

Mark Robertson-Tessi, Robert J. Gillies, Robert A. Gatenby, Alexander R.A. Anderson

Abstract

Histopathologic knowledge that extensive heterogeneity exists between and within tumors has been confirmed and deepened recently by molecular studies. However, the impact of tumor heterogeneity on prognosis and treatment remains as poorly understood as ever. Using a hybrid multiscale mathematical model of tumor growth in vascularized tissue, we investigated the selection pressures exerted by spatial and temporal variations in tumor microenvironment and the resulting phenotypic adaptations. A key component of this model is normal and tumor metabolism and its interaction with microenvironmental factors. The metabolic phenotype of tumor cells is plastic, and microenvironmental selection leads to increased tumor glycolysis and decreased pH. Once this phenotype emerges, the tumor dramatically changes its behavior due to acid-mediated invasion, an effect that depends on both variations in the tumor cell phenotypes and their spatial distribution within the tumor. In early stages of growth, tumors are stratified, with the most aggressive cells developing within the interior of the tumor. These cells then grow to the edge of the tumor and invade into the normal tissue using acidosis. Simulations suggest that diffusible cytotoxic treatments, such as chemotherapy, may increase the metabolic aggressiveness of a tumor due to drug-mediated selection. Chemotherapy removes the metabolic stratification of the tumor and allows more aggressive cells to grow toward blood vessels and normal tissue. Antiangiogenic therapy also selects for aggressive phenotypes due to degradation of the tumor microenvironment, ultimately resulting in a more invasive tumor. In contrast, pH buffer therapy slows down the development of aggressive tumors, but only if administered when the tumor is still stratified. Overall, findings from this model highlight the risks of cytotoxic and antiangiogenic treatments in the context of tumor heterogeneity resulting from a selection for more aggressive behaviors. Cancer Res; 75(8); 1567-79. ©2015 AACR.

Twitter Demographics

The data shown below were collected from the profiles of 35 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
United Kingdom 2 <1%
Germany 2 <1%
France 1 <1%
Unknown 197 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 31%
Researcher 48 23%
Student > Master 22 11%
Student > Doctoral Student 11 5%
Professor > Associate Professor 11 5%
Other 35 17%
Unknown 17 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 54 26%
Biochemistry, Genetics and Molecular Biology 35 17%
Medicine and Dentistry 27 13%
Engineering 18 9%
Mathematics 12 6%
Other 29 14%
Unknown 33 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 26 May 2022.
All research outputs
#796,862
of 21,419,046 outputs
Outputs from Cancer Research
#563
of 17,394 outputs
Outputs of similar age
#11,247
of 243,790 outputs
Outputs of similar age from Cancer Research
#8
of 210 outputs
Altmetric has tracked 21,419,046 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 17,394 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 96% 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 243,790 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 95% of its contemporaries.
We're also able to compare this research output to 210 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 96% of its contemporaries.