PhD Candidate University of Minnesota saint paul, Minnesota, United States
Introduction: In the abstract that I plan to submit, I will introduce an advanced biophysical numerical model of a cell specifically designed to simulate the behavior of T cells. In recent years, there has been increasing interest in immunotherapy methods for treating cancer, particularly for addressing solid tumor cancers that often do not respond to conventional treatments like chemotherapy. T cells are the primary candidates for use in this approach to infiltrate solid tumor sites and eliminate the targeted cancer cells. While the concept is clear, there are numerous challenges when examining the intricacies of the aforementioned process, such as how a cell can migrate through the optimal site and how we can improve the infiltration process. To gain a deeper understanding of this aspect, I will focus on developing a biophysical model to depict mesenchymal and amoeboid modes of migration, which represents a groundbreaking approach in this field.
Materials and
Methods: The use of numerical modeling in the study of cell migration has become increasingly important in the field of cancer bioengineering, particularly as advancements in computer simulations have been made in recent years. I firmly believe that modeling cell migration is essential for several key reasons: 1. Understanding Complex Processes: Cell migration is a highly intricate phenomenon involving numerous factors such as chemical gradients, mechanical cues, and cell-cell interactions. Through modeling, researchers can simplify these multifaceted processes into mathematical or computational frameworks, aiding in the comprehension of the fundamental principles governing cell migration. 2. Prediction and Hypothesis Testing: Models allow researchers to forecast the behavior of migrating cells under different conditions and test hypotheses about the mechanisms driving migration. By manipulating parameters in the model, researchers can simulate various scenarios that may be challenging or even impossible to achieve experimentally. 3. Designing Experiments: Modeling can provide guidance in the design of experiments by suggesting which parameters are most crucial to measure or manipulate. By optimizing experimental conditions based on model predictions, researchers can maximize the information gained from experiments while minimizing resource expenditure. Given the aforementioned points, I intend to develop a biophysical model that can accurately represent a 2D cell environment and its migrational behavior. This will ultimately lead to an enhanced understanding of cell behavior, particularly in in vivo models.
Results, Conclusions, and Discussions: The cell migrational modes for almost all types of cells are typically simulated using two key models, which represent the mesenchymal and amoeboid modes of migration. To create a novel hybrid model, it is recommended to integrate the motor clutch model and the bleb-based motility model, both developed by members of Professor Odde's laboratory. In recent years, bleb-based motility models have been established, but inconsistencies among different models have led to varying interpretations of similar situations. However, a recent study conducted by a team at the University of Minnesota has resolved this ambiguity by employing physical principles and validating the results with previously accepted experimental observations. It is hoped that the effectiveness of the present bleb-based motility model will be better understood through the forthcoming creation of a hybrid model, as suggested in this thesis and future research. Because the model is relatively new, further findings are likely to emerge, which could shed light on the advantages of utilizing this model. The motor-clutch model has undergone extensive testing to evaluate its effectiveness. It was introduced years ago and used in 2008 to interpret cell behavior in sensing their microenvironment's mechanical stiffness. The model's theoretical framework was employed to derive a master equation as an ODE for analytical simulation. Recent studies have used the model for experimental analysis, demonstrating cell migration and the significant impact of clutch stiffness on traction force. By integrating these two models, an innovative hybrid model can be developed to encompass both the amoeboid mode of cell migration and the adhesion to the extracellular substrate following bleb formation. This refined model addresses the limitations of prior models, shedding light on the migrational speed exhibited by a T cell within its local environment.
