Despite immense resources devoted to developing better treatments, glioblastoma multiforme (GBM) patients face a paucity of treatment options and universally have poor outcomes. With treatment, the median survival is fifteen months. Immunotherapy treatment likely holds the greatest potential to combat this terrible disease, and yet many questions remain regarding the relationship between the immune system and the brain, and in particular, the immune system and cancer of the brain. Which components of immune response are indispensable for the immune response to glioblastoma? Why does the immune system ultimately fail to control GBM? Further, how can we leverage the immune response to better treat glioblastoma? This project focuses on interrogating these aspects of glioblastoma, and to effectively do so begins with better mouse models, which is the central thrust of this project. The immune editing hypothesis postulates that cancer cells present peptides derived from their own mutated proteins, which can be recognized as foreign by the immune system. These mutations function as targets, which can mark the tumor for destruction by cytotoxic T cells. During the course of this process, the tumor evolves to become less immunogenic and persists in equilibrium with the immune system. Eventually, the tumor gives rise to less immunogenic targets and effectively becomes invisible to the immune system. At this point, the tumor escapes beyond the immune system?s control and presents clinically. How this process occurs in the central nervous system is less well understood. Human GBMs pose the additional challenge in that they carry low mutational burden, and hence have few mutations to target. Current mouse models of GBM either have high mutational burden, or low mutational burden but are for various reasons unsuitable to study tumor-immune system interactions. The model for this project will use lentivirus as a means to deliver both oncogenic proteins and Cre-recombinase to excise loxP flanked tumor-suppressors in a precise way, in immunologically mature mice, of a pure genetic background. This autochthonous, orthotopic pre-clinical model will more faithfully recapitulate the disease as it occurs in humans. This system will also be employed to develop a hypermutated model of recurrent GBM to establish the relationship between mutational burden and checkpoint blockade sensitivity in CNS tumors. These models will be superior for simulating the disease seen in humans because of their low mutational burden, because the genetic targeting is precise, because how the immune system will ?see? the tumor is similar to the human disease, and because of the autochthonous nature of tumor formation. These genetically engineered mouse models of GBM will answer fundamental questions regarding how the immune system interacts with GBM, will establish the relationship between mutational burden and checkpoint blockade sensitivity of CNS tumors, and will hopefully lead to development of more effective treatments.

Public Health Relevance

Despite tremendous funding and research devoted toward the study of glioblastoma multiforme (GBM), the disease remains incurable, and the prognosis grim: median survival is less than fifteen months. The goal of this project is develop better mouse models of malignant glioma, and to use them to better understand how the immune system interacts with the tumor. Understanding how the immune system interacts with a true-to-disease model of GBM will hopefully lead to development of more effective immunotherapies against GBM, which could lead to breakthroughs in survival, similar to other once-thought incurable cancers now being effectively treated with immunotherapies.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
1F30CA236454-01A1
Application #
9834190
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Damico, Mark W
Project Start
2019-07-01
Project End
2022-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Washington University
Department
Neurosurgery
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130