Modeling Glioblastoma's Effect on Neural Networks using Brain Organoids Skip to main content
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2024 Abstracts

Modeling Glioblastoma's Effect on Neural Networks using Brain Organoids

Authors: Jude Werth
Mentors: Alex Shcheglovitov
Insitution: University of Utah

Glioblastoma (GBM) is the deadliest brain tumor that affects more than 10,000 people a year. Unfortunately, our understanding of the mechanisms disrupted by GBM is extremely limited. We are unable to safely manipulate brain cells in live patients, and the complexity of human brain networks are difficult to recapitulate in animals. This study employs brain organoids, derived from induced Pluripotent Stem Cells (iPSCs), to model the impact of GBM on neural activity. Organoid batches, grown under normal conditions and co-cultured with GBM cells, were monitored using microelectrode arrays (MEA) to record power in frequency bands. Over time, drugs influencing neural activity were introduced. Significant behavioral distinctions were observed between control and GBM-cultured organoids. Under Bicuculline and Tetrodotoxin, power in GBM organoids exhibited dramatic changes compared to the minimal difference in control organoids. Conversely, 4-Aminopyridine induced increased high-frequency activity exclusively in control organoids. Correlating power in frequency bands with spike activity, this study provides insight on how brain tumors influence neural networks, furthering disease comprehension to eventually develop effective treatment for patients.