Abstract : Several studies have demonstrated that mathematical and computational data analysis models are required to obtain a systematic understanding of the diseases and find effective treatments. As a result, many mathematical models using both stochastic and deterministic methods have been developed to study the evolutionary processes of the diseases' initiation and progression. Some of the results of these computational models were used to predict the outcome of various drugs to obtain optimal treatment strategies. This mini-symposium will bring together scientists who are interested in the mathematical modeling of different biomedical diseases, including COVID-19, AIDs, TB, cancer, etc.
[00317] Role of senescent tumor cells and macrophages in building a cytokine shield in the tumor microenvironment: mathematical modeling
Format : Talk at Waseda University
Author(s) :
Yangjin Kim (Konkuk University)
Junho Lee (B)
Chaeyoung Lee (Korea University)
Sean Lawler (Brown University)
Abstract : Cellular senescence can induce dual effects (promotion or inhibition) on cancer progression. While immune cells naturally respond and migrate toward various chemotactic sources from the tumor mass, various factors including senescent tumor cells (STCs) in the tumor microenvironment (TME) may affect this chemotactic movement. In this work, we investigate the mutual interactions between the tumor cells and the immune cells (T cells and macrophages) that either inhibit or facilitate tumor growth by developing a mathematical model that consists of taxis-reaction-diffusion equations and receptor kinetics for the key players in the interaction network. We first apply a mathematical model to a transwell Boyden chamber invasion assay used in the experiments to illustrate that STCs can play a pivotal role in negating immune attack through tight regulation of intra- and extra-cellular signaling molecules. In particular, we show that senescent tumor cells in cell cycle arrest can block intratumoral infiltration of CD8+ T cells by secreting a high level of CXCL12, which leads to significant reduction its receptors, CXCR4, on T cells, and thus impaired chemotaxis. Macrophages also play an important role in mediating or inhibiting given signaling pathways between different cells in TME. The predictions of nonlinear responses to CXCL12 were in good agreement with experimental data. We tested several hypotheses on immune-tumor interactions under various biophysical- and biochemical- conditions in the tumor microenvironment and developed new concepts for anti-tumor strategies targeting senescence induced immune impairment.
[00373] Patch formation driven by stochastic effects of interaction between viruses and defective interfering particles
Format : Talk at Waseda University
Author(s) :
Qiantong Liang (City University of Hong Kong)
Wing-Cheong Lo (City University of Hong Kong)
Abstract : We develop a model with a new hybrid method to study the spatial-temporal dynamics of viruses and DIPs co-infections within hosts. We present two scenarios of virus production and compare the results from deterministic and stochastic models to demonstrate how the stochastic effect is involved in the spatial dynamics of virus transmission. Our simulations demonstrate that DIPs can slow down the growth of virus particles and make the spread of virus more patchy.
[01228] Modeling about prediction and improvement of therapeutic efficacy of immune checkpoint inhibitors
Format : Talk at Waseda University
Author(s) :
Xiulan Lai (Renmin University of China)
Abstract : Immune checkpoint inhibitors have been shown to be highly successful against some solid metastatic malignancies, but the overall patient response rate is limited due to the interpatient heterogeneity. In this project, we explored the effect of favorable and unfavorable gut bacteria on the therapeutic efficacy of anti-PD-1 against cancer by modeling the tumor-immune-gut microbiome interactions, and further examined the predictive markers of responders and non-responders to anti-PD-1. The dynamics alteration of PD-L1 expression status during cancer evolution and treatment are also obstacles for PD-1/PD-L1 inhibitors. We established a comprehensive modeling and computational framework for estimating the dynamic alternation of PD-L1 heterogeneity during cancer progression and treatment, and predicting the overall survival of patients.
[01252] Travelling waves of a new glioma invasion model.
Format : Talk at Waseda University
Author(s) :
Ryan Thiessen (University of Alberta)
Abstract : Recently a detailed study of in-vivo glioma invasion patterns in the healthy brain tissue of living mice shows that specialized cancer cells build a network similar to a healthy brain neuronal network. We develop a model for this new phenomenon via a kinetic formulation. After making some simplifying assumptions, we arrive at a reaction-diffusion model. In this talk, I will explore travelling waves for the simplified new glioblastoma model.
[01194] The role of the autoregulation mechanism in hypertension and hypotension in humans
Format : Talk at Waseda University
Author(s) :
Radu C Cascaval (University of Colorado Colorado Springs)
Abstract : We present a nonlinear model for the propagation of the pressure and flow velocity waves in the human cardiovascular system, including deep learning tools with available physiological data. This model is used for understanding the system-level dynamics of the pressure and flow rates. This time-domain analysis is best to describe time-dependent controls, collectively known as the autoregulation mechanism. We discuss an application of our model to the study of the hypertension and hypotension.
[01215] Collaborative research toward data driven mathematical modeling of cancer to arrive at effective treatments
Format : Talk at Waseda University
Author(s) :
Leili Shahriyari (University of Massachusetts Amherst)
Abstract : Cancer is a complex disease with many unknown features. The evolution of tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. To overcome some of the outstanding challenges of mathematical modeling of cancer, we have utilized and integrated several computational techniques. Importantly, in collaboration with scientists with diverse backgrounds, we have used patients’ data and rich spatio-temporal mouse data to develop data-driven mathematical models for tumors’ progression. We believe a collaborative model for conducting research and sharing resources, including codes, data, and results would improve our chances to arrive at more effective treatments and ultimately eliminate cancer as a major health problem for this and future generations. In this talk, I will provide an overview of some of our recent collaborative works and outline several outstanding challenges and possible next steps to address them.
[01334] Phase-field model of mechanical stability of blood clot
Format : Online Talk on Zoom
Author(s) :
Zhiliang Xu (University of Notre Dame)
Abstract : Deformation and detachment of blood clot (thrombus) under different flow conditions are studied. The fibrin and activated platelets are assumed to concentrate in the core of a thrombus and less-activated platelets are assumed to concentrate in the shell region near the boundary of a thrombus. Interactions among different components are simulated by using Cahn-Hilliard type systems of equations. The macroscopic motion of fluid is described by incompressible Navier-Stokes equations with terms representing viscos, elastic and phase interaction forces as well as porous media drag force. Model simulations predict that the permeability and porosity o of the shell region are shown to effect the stalbility of the blood clot. The stablity of the red blood cell cavity at different position in the blood clot are also illustrated.
