Abstract 776: Multiscale treatment response model for triple-negative breast cancer linking drug pharmacokinetics to tumor cell population dynamics
Authors: Matthew T. McKenna, Stephanie L. Barnes, Abigail Searfoss, Darren R. Tyson, Erin Rericha, Vito Quaranta, Thomas E. Yankeelov
Journal: Cancer Research (2016)

Abstract Introduction The goal of this study is to establish a predictive model of cytotoxic therapy that incorporates in vitro drug pharmacokinetics and cell-scale therapy response data, on a cell-line specific basis. We report on a series of time-resolved fluorescence microscopy experiments to characterize the uptake of doxorubicin and its effect on the population dynamics of MDA-MB-231 cells, a model of triple negative breast cancer. Experimental Design We leveraged the intrinsic fluorescence of doxorubicin to measure its uptake by MDA-MB-231 cells. Cells, labeled with a fluorescent nuclear marker, were seeded in microtiter plates and incubated with doxorubicin concentrations ranging from 10 nM to 10 μM for 6, 12, or 24 hours. These plates were imaged daily via bright field and fluorescent microscopy after addition of doxorubicin. Nuclei were segmented and automatically counted to quantify cell population size. Counts were normalized to population size at time of treatment and converted to population doublings. On a separate channel, extracellular, cytoplasmic, and nuclear doxorubicin fluorescence were quantified. A compartment model describing the movement of doxorubicin from the extracellular space into cells was fit to these data. We then constructed a cell treatment response model and fit it, coupled with the compartment model, to the population data using MATLAB. Results MDA-MB-231 cellular response to doxorubicin was tightly linked to both drug concentration and exposure time. Higher doses (&amp;gt; 1 μM) invariably induced rapid cell death. Smaller doses (&amp;lt; 1 μM) induced a concentration-dependent nonlinear response defined by an initial increase in population size that, depending on exposure time, was followed by a protracted decrease in cell number. For example, when treated with 156 nM for 6, 12, and 24 hours, we observed, respectively, an average of 2.6, 2.1, and 0.67 population doublings over the first 150 hours after treatment (p &amp;lt; 0.05 among groups). These populations then either held stable or receded out to 400 hours, when we observed net population doublings of 2.6, 1.7, and 0.037, respectively (p &amp;lt; 0.05). Untreated cells followed a logistic growth pattern, with an average total of 4.4 population doublings. Conclusion These time-resolved treatment protocols replicate clinically observed pharmacokinetics of cytotoxic therapies more closely than the constant concentrations in previous dose-response assays. By explicitly considering both drug and population dynamics, our mathematical model enables exploration, in silico, of treatment protocols intractable experimentally. Predictions from model simulations can then be tested experimentally, hopefully allowing for computationally-optimized and experimentally validated treatment regimens that maximize cytotoxic effects of doxorubicin. Citation Format: Matthew T. McKenna, Stephanie L. Barnes, Abigail Searfoss, Darren R. Tyson, Erin Rericha, Vito Quaranta, Thomas E. Yankeelov. Multiscale treatment response model for triple-negative breast cancer linking drug pharmacokinetics to tumor cell population dynamics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 776.