Modeling cell adhesion and proliferation: a cellular-automata based approach

Integration of quantitative methods and mathematical approaches for the modeling of cancer cell proliferation dynamics

Physiological processes rely on the control of cell proliferation, and the dysregulation of these processes underlies various pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-laboratory studies may be integrated with different mathematical modeling approaches to aid the interpretation of the results and to enable the prediction of cell behaviors, specifically in the context of cancer.

Electrospun Nanofibrils Surface-Decorated with Photo-Cross-Linked Hyaluronic Acid for Cell-Directed Assembly

Hyaluronic acid (HA) was chemically immobilized on the surface of electrospun nanofibrils to form a cell/NF complex. Poly(caprolactone) (PCL) was electrospun into nanofibrous mats that were subsequently aminolyzed into nanofibrils. The aminolyzed nanofibrils were surface-decorated with methacrylated HA via Michael type addtion and by photo-cross-linking. Fourier transform infrared spectroscopy revealed the presence of HA on the surface of the nanofibrils. The thermogravimetric and colorimetric analyses indicate that the degree of HA immobilization could be varied by varying the photo-cross-linking duration. Thus, on increasing the photo-cross-linking duration, the swelling ratios increased gradually, and the surface charge of the decorated nanofibrils decreased. NIH3T3 cells and surface-decorated nanofibrils spontaneously assembled into the cell/NF complex. A higher degree of surface-immobilized HA enhanced cell viability and proliferation compared to nanofibrils without surface-immobilized HA. Thus, we envision that HA-immobilized nanofibrils can be employed as a tissue-engineering matrix to control cell proliferation and differentiation.

Engineering cell-substrate interactions on porous membranes for microphysiological systems

Microphysiological systems are now widely used to recapitulate physiological and pathological microenvironments in order to study and understand a variety of cellular processes as well as drug delivery and stem cell differentiation. Central to many of these systems are porous membranes that enable tissue barrier formation as well as compartmentalization while still facilitating small molecule diffusion, cellular transmigration and cell-cell communication. The role or impact of porous membranes on the cells cultured upon them has not been widely studied or reviewed. Although many chemical and physical substrate characteristics have been shown to be effective in controlling and directing cellular behavior, the influence of pore characteristics and the ability to engineer porous membranes to influence these responses is not fully understood. In this mini-review, we show that many studies point to a multiphasic cell-substrate response, where increasing pore sizes and pore-pore spacing generally leads to improved cell-substrate interactions. However, the smallest pores in the nano-scale sometimes promote the strongest cell-substrate interactions, while the very largest micron-scale pores hinder cell-substrate interactions. This synopsis provides an insight into the importance of membrane pores in controlling cellular responses, and may help with the design and utilization of porous membranes for induction of desired cell processes in the development of biomimetic platforms.

In vitro Fourier transform infrared spectroscopic study of the effect of glycerol on the uptake of beclomethasone dipropionate in living respiratory cells

The quantification of drug in living cells is of increasing interest in pharmaceutical research because of its importance in understanding drug efficacy and toxicity. Label-free in situ measurement methods are advantageous for their ability to obtain chemical and time profiles without the need of labelling or extraction steps. We have previously shown that Fourier transform infrared (FTIR) spectroscopy has the potential to quantify drug in situ within living cells at micromolar level when a simple solution of drug was added to the medium. The purpose of this study was to demonstrate that the approach can evaluate more complex systems such as the effect of membrane modification by a formulation on drug uptakes. The inhaled corticosteroid, beclomethasone dipropionate (BDP), in Calu-3 respiratory epithelial cells in the absence and presence of glycerol, an excipient in some inhaled medicines was used as the model system. The FTIR method was first validated for limit of detection (LOD) and quantification (LOQ) according to published guidelines and the LOQ was found to be ∼ 20 μM, good enough to quantify BDP in the living cell. The uptake of BDP by living Calu-3 cells was found to be reduced in the presence of glycerol as expected due to the stiffening of the cell membrane by the presence of glycerol in the formulation. This study demonstrates the valuable analytical capability of live-cell FTIR to study the effect of formulation on drug transport in lungs and to evaluate drug availability to intracellular targets. We conclude that FTIR has potential to contribute widely at the frontier of live-cell studies.

Modeling Living Cells Within Microfluidic Systems Using Cellular Automata Models

Several computational models, both continuum and discrete, allow for the simulation of collective cell behaviors in connection with challenges linked to disease modeling and understanding. Normally, discrete cell modelling employs quasi-infinite or boundary-less 2D lattices, hence modeling collective cell behaviors in Petri dish-like environments. The advent of lab- and organ-on-a-chip devices proves that the information obtained from 2D cell cultures, upon Petri dishes, differs importantly from the results obtained in more biomimetic micro-fluidic environments, made of interconnected chambers and channels. However, discrete cell modelling within lab- and organ-on-a-chip devices, to our knowledge, is not yet found in the literature, although it may prove useful for designing and optimizing these types of systems. Consequently, in this study we focus on the establishment of a direct connection between the computer-aided designs (CAD) of microfluidic systems, especially labs- and organs-on-chips (and their multi-chamber and multi-channel structures), and the lattices for discrete cell modeling approaches aimed at the simulation of collective cell interactions, whose boundaries are defined directly from the CAD models. We illustrate the proposal using a quite straightforward cellular automata model, apply it to simulating cells with different growth rates, within a selected set of microsystem designs, and validate it by tuning the growth rates with the support of cell culture experiments and by checking the results with a real microfluidic system.

VEGFR1 promotes cell migration and proliferation through PLCγ and PI3K pathways

The ability to control vascular endothelial growth factor (VEGF) signaling offers promising therapeutic potential for vascular diseases and cancer. Despite this promise, VEGF-targeted therapies are not clinically effective for many pathologies, such as breast cancer. VEGFR1 has recently emerged as a predictive biomarker for anti-VEGF efficacy, implying a functional VEGFR1 role beyond its classically defined decoy receptor status. Here we introduce a computational approach that accurately predicts cellular responses elicited via VEGFR1 signaling. Aligned with our model prediction, we show empirically that VEGFR1 promotes macrophage migration through PLCγ and PI3K pathways and promotes macrophage proliferation through a PLCγ pathway. These results provide new insight into the basic function of VEGFR1 signaling while offering a computational platform to quantify signaling of any receptor.