A major obstacle to successful pharmacological treatment of brain tumors is the blood-brain barrier (BBB), which prevents most anti-cancer agents from entering the brain parenchyma in amounts sufficient to eradicate tumors. Neural stem cells (NSCs)?immature cells that can regenerate any type of cell in the nervous system?offer a potential solution to treating brain tumors. This is because NSCs can circumvent the BBB and migrate to areas of damage in the central nervous system (CNS), including tumors, stroke and wound injuries. As tools for significantly improving the survival of brain tumor patients, NSCs have been investigated as delivery vehicles for prodrug activating enzymes, nanoparticles, and other anti-cancer agents in the context of intracranial (IC), intravenous (IV), and intranasal (IN) delivery. NSCs have been engineered to deliver anti- cancer agents, demonstrating therapeutic efficacy in preclinical models of several types of primary and metastatic brain tumors, which has led to first-in-human clinical trials of NSC-mediated therapy for glioma patients. However, in order for NSC therapy (by any delivery method) to be effective, a sufficient number of viable cells must reach the diseased or damaged area(s) in the brain, but the paths that the NSCs take to the tumors, as well as the location of tumors within the brain may affect the ultimate number of viable cells that reach the tumor. In our previous preclinical studies using 3D reconstructions of serial tissue sections, we have demonstrated that NSCs delivered via IN or IC methods can migrate towards and reach brain tumor sites, and, post hoc, that NSCs are found migrating along white matter tracts. At present, we lack a method to predict a priori the paths taken by NSCs in novel settings. We hypothesize that computational analyses of tissue anisotropy will identify white matter tracts amenable to NSC migration, and provide the ability to predict routes of NSC migration and biodistribution within the brain. The goal of this application is to develop and validate a novel computational model using tissue anisotropy to predict migration paths of NSCs to brain tumor sites after IC or IN administration.
The Specific Aims are:
Specific Aim 1 : To develop and apply computational models of NSC migration in the brain based on tissue anisotropy and route finding algorithms.
Specific Aim 2 : To validate the computational method in a pilot study in brain tumor-bearing mice. The successful application of this approach will provide a way to predict the numbers of NSCs that will reach a tumor depending on the injected dose and location within the brain. This method could then be widely used in the areas of brain tumor therapy and regenerative medicine as a possible way to identify patients that are good candidates for NSC- based therapy depending on tumor location, or the best NSC administration method for a patient.
A major obstacle to successful treatment of brain tumors is the blood-brain barrier, which prevents most anti- cancer agents from entering the brain in amounts sufficient to eradicate tumors. Neural stem cells (NSCs) offer a potential solution to treating brain tumors by passing the blood-brain barrier and delivering anti-cancer agents to the tumor. The proposed studies will use computational analyses of brain tissue structures and route-finding algorithms to identify paths in the brain amenable to NSC migration, which will allow us to predict routes of NSC migration and distribution within the brain to accelerate clinical translation of NSC therapies and potentially design personalized NSC-based therapies based on characteristics of an individual's tumor.
| Rockne, Russell C; Adhikarla, Vikram; Tsaturyan, Lusine et al. (2018) Long-term stability and computational analysis of migration patterns of L-MYC immortalized neural stem cells in the brain. PLoS One 13:e0199967 |
