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IEEE Trans Biomed Eng. 2017 Mar;64(3):512-518. doi: 10.1109/TBME.2016.2623564. Epub 2016 Nov 1.

Aggregation Effects and Population-Based Dynamics as a Source of Therapy Resistance in Cancer.

Abstract

OBJECTIVE:

Evolution of resistance allows cancer cells to adapt and continue proliferating even when therapy is initially very effective. Most investigations of treatment resistance focus on the adaptive phenotypic properties of individual cells. We propose that the resistance of a single cell to therapy may extend beyond its own phenotypic and molecular properties and be influenced by the phenotypic properties of surrounding cells and variations in cell density. Similar variation exists in population densities of animals living in groups and can significantly affect the outcome of an external threat.

METHODS:

We investigate aggregation effects in cancer therapy using Darwinian models that integrate phenotypic properties of individual cells and common population effects found in nature to simulate the dynamics of resistance and sensitivity in the diverse cellular environments within cancers.

RESULTS:

We demonstrate that the density of cancer cell populations can profoundly influence response to chemotherapy independent of the properties of individual cells. Most commonly, these aggregation effects benefit the tumor allowing cells to survive even with phenotypic properties that would render them highly vulnerable to therapy in the absence of population effects.

CONCLUSION:

We demonstrate aggregation effects likely play a significant role in conferring resistance to therapy on tumor cells that would otherwise be sensitive to treatment.

SIGNIFICANCE:

The potential role of aggregation in outcomes from cancer therapy has not been previously investigated. Our results demonstrate these dynamics may play a key role in resistance to therapy and could be used to design evolutionarily-enlightened therapies that exploit aggregation effects to improve treatment outcomes.

PMID:
28113286
PMCID:
PMC5438296
DOI:
10.1109/TBME.2016.2623564
[Indexed for MEDLINE]
Free PMC Article

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