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Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an
Kaitlyn E Johnson1, Grant Howard1, William Mo1
1Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, United States of America.
Plos Biology
|August 6, 2019
Summary
Cancer cells exhibit cooperative growth at low densities, challenging traditional exponential models. This Allee effect, where birth rates increase with cell numbers, is crucial for understanding early tumor expansion.
Area of Science:
- Oncology
- Mathematical Biology
- Ecology
Background:
- Traditional cancer growth models assume exponential expansion at low densities, with growth slowing only at high densities due to resource limitation.
- Recent observations suggest tumor growth rates can increase with cell numbers, similar to the Allee effect in ecology.
- Preclinical and clinical data are often limited by detection thresholds and confounding factors like the tumor microenvironment.
Purpose of the Study:
- To investigate the presence of an Allee effect in cancer cell growth at low densities using controlled in vitro experiments.
- To develop and apply a stochastic modeling framework to differentiate Allee effects from random population fluctuations.
- To analyze longitudinal cell proliferation data to determine the best-fit growth model for cancer cells.
Main Methods:
- Proposed a stochastic modeling framework to analyze cancer cell population dynamics.
- Utilized the moment approach for stochastic parameter estimation to calibrate growth models.
- Applied the framework to in vitro proliferation data of BT-474 luminal B breast cancer cells.
Main Results:
- The Allee effect model best described the observed cancer cell population growth kinetics.
- Found that the birth rate of tumor cells increases with cell number at low population densities.
- Demonstrated the utility of the stochastic modeling framework in identifying cooperative growth patterns.
Conclusions:
- Cooperative behavior, or the Allee effect, plays a significant role in cancer cell proliferation at low densities.
- This finding has implications for understanding the early growth stages of emerging and relapsed tumors.
- The developed stochastic modeling approach can help elucidate complex cancer growth dynamics.
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