Mathematical modeling to study combination strategies for neural stem cell therapy in glioblastoma

Abstract

Neural stem cells (NSCs) are a promising treatment platform due to their ability to cross the restrictive blood-brain barrier and migrate toward damaged regions of the brain. These properties can be leveraged to target brain tumors, as NSCs can infiltrate tumor lesions and deliver therapeutic agents such as drugs, oncolytic viruses, and genetic materials. Despite the advantages of NSCs, translational challenges remain, including patient-specific chemotactic signaling and immune responses, variability in migration and localization at tumor sites, and optimization of delivery strategies. In this work, we focus on intranasal delivery of NSCs and combination strategies for the treatment of brain cancer. To investigate strategies for improving NSC arrival at the tumor site, we developed a hybrid mathematical model of NSC migration that couples an agent-based model with a partial differential equation, where cell motion is guided by the spatial dynamics of chemoattractants. Using data collected from a murine model and our mathematical model, we {investigate treatment-motivated downstream effects associated with three combination strategies:} (1) IL-10 pretreatment, (2) CXCL12 pretreatment, and (3) radiotherapy. We find that IL-10 pretreatment improves NSC arrival numbers at tumor only under the Gaussian chemoattractant profile, whereas CXCL12 pretreatment moderately improves arrival numbers when the tumor is located in the anterior brain. Radiotherapy significantly enhances the tumor arrival under uniform profiles. These simulation studies suggest that both treatment strategies and chemoattractant distribution influence intranasal NSC delivery, and the proposed model can be used to predict how targeted modulation of chemotactic signaling and tissue-guided migration may improve delivery outcomes.