# Hong Proj-4

> **NIH NIH P20** · DARTMOUTH COLLEGE · 2024 · $226,103

## Abstract

PROJECT SUMMARY/ABSTRACT
Seizures are a common, severe neurologic symptom of brain tumors with up to 80% of patients experiencing at
least one seizure. Recurrent seizures, termed brain-tumor-related epilepsy (BTRE), develop in half of brain tumor
patients and are often refractory to medical management. Poorly controlled epilepsy is the leading risk-factor for
long-term disability in brain tumor patients and complicates the course of treatment due to drug toxicities, loss of
driving privileges, and decreased quality of life. Further, an emerging body of work investigating neuronal
regulation of glioma growth suggests that epileptiform activity promotes tumor proliferation and invasion.
Successful intervention to stop seizures in patients would profoundly reduce neurologic morbidity and may halt
tumor progression. However, current first-line therapy for BTRE, the drug Leviteracetam, a synaptic release
inhibitor, fails to suppress seizures in half of patients. A fundamental shift in our approach to treatment of BTRE
is greatly needed.
 Recent studies on the pathogenesis of tumor-related epilepsy have uncovered novel roles for the brain
tumor microenvironment (TME), including tumor-stromal and tumor-neuron interactions that result in bi-
directional, synergistic efforts to re-sculpt the molecular structure of the TME, resulting in neuronal dysfunction
and a feed-forward loop of loss of inhibition, repeated seizures, and tumor progression. In particular, the
perineuronal net (PNN) has been shown to be degraded by gliomas, resulting in dysregulation of inhibitory
interneurons in the adjacent cortex. The TME is a novel and potentially powerful therapeutic target in BTRE;
however, the molecular and cellular mechanisms connecting tumor microenvironment to clinical seizures in
patients remain undefined.
 To better understand seizure onset in patients with brain tumors, this project will perform digital spatial
profiling (DSP), an automated system for multiplexed, spatially-linked RNA transcript and protein expression
quantification, and Visium 10x Single-nuclei RNA sequencing on brain tumor specimens to evaluate PNN
structure and composition in the TME. The project will then apply machine-learning approaches to analyze these
high-dimensional data in order to identify PNN features that relate to a clinical history of seizures. This aim will
test the hypothesis that tumor-related PNN degradation in patients is associated with severe neurologic
symptoms. It will also result in major development of novel histologic and computational techniques for evaluation
of PNN structure and function that can be broadly applied to other, similarly complex biomedical datasets.
 Completion of these aims will help the Project Leader and research team to better understand how brain
pathologies affect PNNs in patients, generate new biological resources and technologies for the study of human
PNNs, and provide evidence to support preserving or restoring the PNN as a novel, more ...

## Key facts

- **NIH application ID:** 10852733
- **Project number:** 2P20GM130454-06
- **Recipient organization:** DARTMOUTH COLLEGE
- **Principal Investigator:** Jennifer Hong
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $226,103
- **Award type:** 2
- **Project period:** 2019-08-01 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10852733

## Citation

> US National Institutes of Health, RePORTER application 10852733, Hong Proj-4 (2P20GM130454-06). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10852733. Licensed CC0.

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