Drug Delivery through the Blood-Brain Barrier through Use of Vascular Cell Adhesion Molecule 1- Targeted Nanoparticles

The blood brain barrier (BBB) is a semi-permeable membrane separating the brain from the bloodstream, preventing many drugs that treat neurological diseases, such as Alzheimer’s and Parkinson’s, from reaching the brain. Our project aimed to create a novel drug delivery system targeting the brain during neural inflammation. We developed a cationic solid lipid nanoparticle (CSLN) complex composed of cationic nanoparticles, biotin, streptavidin, and anti-vascular cell adhesion molecule-1 (anti- VCAM-1) antibodies. The anti-VCAM-1 antibody is used to target VCAM-1, a cell adhesion protein found on the BBB endothelium. VCAM-1 expression is elevated in the presence of inflammatory molecules, such as tumor necrosis factor-alpha (TNF- α). Through the use of a simple BBB model, results showed that our novel drug delivery system experienced some level of success in targeting the brain inflammation due to increasing TNF-α concentrations. This is promising for drug delivery research and provides support for VCAM-1 targeting using more robust and complex BBB models.

ROLE OF ICAM-1-MEDIATED ENDOCYTOSIS IN ENDOTHELIAL FUNCTION AND IMPLICATIONS FOR CARRIER-ASSISTED DRUG DELIVERY

Intercellular adhesion molecule 1 (ICAM-1) is a transmembrane protein found on the surface of vascular endothelial cells (ECs). Its expression is upregulated at inflammatory sites, allowing for targeted delivery of therapeutics using ICAM-1-binding drug carriers. Engagement of multiple copies of ICAM-1 by these drug carriers induces cell adhesion molecule (CAM)-mediated endocytosis, which results in trafficking of carriers to lysosomes and across ECs. Knowledge about the regulation behind CAM-mediated endocytosis can help improve drug delivery, but questions remain about these regulatory mechanisms. Furthermore, little is known about the natural function of this endocytic pathway. To address these gaps in knowledge, we focused on two natural binding partners of ICAM-1 that potentially elicit CAM-mediated endocytosis: leukocytes (which bind ICAM-1 via β₂ integrins) and fibrin polymers (a main component of blood clots which binds ICAM-1 via the γ3 sequence). First, inspired by properties of these natural binding partners, we varied the size and targeting moiety of model drug carriers to determine how these parameters affect CAM-mediated endocytosis. Increasing ICAM-1-targeted carrier size slowed carrier uptake kinetics, reduced carrier trafficking to lysosomes, and increased carrier transport across ECs. Changing targeting moieties from antibodies to peptides decreased particle binding and uptake, lowered trafficking to lysosomes, and increased transport across ECs. Second, using cell culture models of leukocyte/EC interactions, inhibiting regulatory elements of the CAM-mediated pathway disrupted leukocyte sampling, a process crucial to leukocyte crossing of endothelial layers (transmigration). This inhibition also decreased leukocyte transmigration across ECs, specifically through the transcellular route, which occurs through a single EC without disassembly of cell-cell junctions. Third, fibrin meshes, which mimic blood clot fragments/remnants, bound to ECs at ICAM-1-enriched sites and were internalized by the endothelium. Inhibiting the CAM-mediated pathway disrupted this uptake. Following endocytosis, fibrin meshes trafficked to lysosomes where they were degraded. In mouse models, CAM-mediated endocytosis of fibrin meshes appeared to remove fibrin remnants at the endothelial surface, preventing re-initiation of the coagulation cascade. Overall, these results support a link between CAM-mediated endocytosis and leukocyte transmigration as well as uptake of fibrin materials by ECs. Furthermore, these results will guide the future design of ICAM-1-targeted carrier-assisted therapies.

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.