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Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

Overview of attention for article published in Frontiers in oncology, August 2017
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment
Published in
Frontiers in oncology, August 2017
DOI 10.3389/fonc.2017.00189
Pubmed ID
Authors

Alexander Lorz, Dana-Adriana Botesteanu, Doron Levy

Abstract

Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in "age," i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug's effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large "switch-on/switch-off" increase in the average cell-cycle length maintains an active cell population in the long term, with oscillating numbers of proliferative cells and a relatively constant quiescent cell number.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Researcher 3 14%
Student > Ph. D. Student 3 14%
Other 2 9%
Student > Bachelor 2 9%
Other 3 14%
Unknown 5 23%
Readers by discipline Count As %
Mathematics 6 27%
Agricultural and Biological Sciences 4 18%
Biochemistry, Genetics and Molecular Biology 3 14%
Engineering 2 9%
Sports and Recreations 1 5%
Other 0 0%
Unknown 6 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 September 2023.
All research outputs
#8,436,572
of 25,806,080 outputs
Outputs from Frontiers in oncology
#3,158
of 22,805 outputs
Outputs of similar age
#121,270
of 324,674 outputs
Outputs of similar age from Frontiers in oncology
#26
of 94 outputs
Altmetric has tracked 25,806,080 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 22,805 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 85% 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 324,674 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 94 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 68% of its contemporaries.