Abstract B21: Using computational modeling to quantify targeted agent binding and internalization in pancreatic cancers
Authors: Karolak Aleksandra , Estrella Veronica , Chen Tingan , Huynh Amanda , Morse David , Rejniak Katarzyna 
Published: May 2016

Abstract
The pancreatic adenocarcinoma is one of the most deadly cancers with only 6% overall 5-year survival rate. Since the current therapies fail to provide successful results, the improvement of techniques for early detection, predicting of treatment efficacy and monitoring of tumor spread during and after surgical procedures remain under focused research. The purpose of this study is to develop a novel method to assess behavior (diffusion and binding within the tissues) of imaging agents targeted to pancreatic cancer cells. Our long-term goal is to design a prospective tool for the prediction of targeted imaging agent peak concentration and cellular uptake based on individual patient data.
The toll-like receptor 2 (TLR2) is known to play an important role in the immune system response. In addition, our team reported that TLR2 is a bona fide cell-surface marker for targeting pancreatic cancer. TLR2 recognizes a vast number of biomolecules, including lipoproteins, such as designed by our team, novel TLR2 ligand (TLR2L). Recent development of an intravital fluorescence microscopy method allowed for the real time in vivo imaging of the TLR2L conjugated to near-infrared fluorescent dye, Cyanine 5 (TLR2L-Cy5) and its penetration through the tissue of pancreatic adenocarcinoma tumor xenografts in mice with endogenous expression of TLR2. In order to quantify the space- and time-dependent dynamics of TLR2L we combined intravital dorsal window chamber experiments with computational modeling of TLR2L-Cy5 diffusion and internalization following intravenous administration. Our computational model accounts for an explicitly defined tissue morphology composed of individual tumor cells, extracellular matrix interpenetrated by the interstitial fluid, and tumor vasculature. We also model individual molecules of a fluorescent imaging agent that extravasate via transmural influx from blood capillaries, spread through the tumor and become internalized by the cells. The process of agonist binding to the receptor is modeled by trapping the particle by the near-by cell boundary receptor, which mimics the distance dependent electrostatic and hydrophobic interactions initiating the recognition and binding in vivo.
Our studies led to quantification of the TLR2L-Cy5 intratumoral transport including agent extravasation, diffusion and intracellular accumulation in relation to tumor tissue structure and vascular architecture. The performed computational simulations allowed for detailed continuous in time assessment of the targeted imaging agent penetration on the microscopic (cell-to-tissue) level. The calibrated in silico model revealed the time-dependent dynamics of TLR2L-Cy5 agent binding, internalization and intracellular distribution. Our quantitative approach also showed a non-uniform spatial saturation of the TLR2L-Cy5 on the plasma membrane and inside the cell. Moreover, continuous simulations allowed for prediction of the maximum concentration peak in the extracellular matrix and for the uptake peak in individual cells. In addition to quantitative analysis, we provide novel (two- and three-dimensional) visualization tools for imaging agent dynamical penetration, membrane binding and receptor-mediated endocytosis process in pancreatic cells.
In conclusion, we present an interdisciplinary approach to quantify diffusion and cellular uptake of an imaging agent targeted to pancreatic cancer cell lines expressing the TLR2 receptor. This integrated approach can be used in the future for the development of other targeted imaging and therapeutic agents, for other solid tumors, and for optimizing the administration schedules and time points for data collection from individual human tumor xenografts in order to improve treatment efficacy.
Citation Format: Aleksandra Karolak, Veronica Estrella, Tingan Chen, Amanda Huynh, David Morse, Katarzyna Rejniak. Using computational modeling to quantify targeted agent binding and internalization in pancreatic cancers. [abstract]. In: Proceedings of the Fourth AACR International Conference on Frontiers in Basic Cancer Research; 2015 Oct 23-26; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2016;76(3 Suppl):Abstract nr B21.