# Research Testbed 2

> **NIH NIH U54** · UNIVERSITY OF MINNESOTA · 2024 · $331,163

## Abstract

Abstract
Brain tumors remain among the most malignant and deadly cancers, with adult glioblastoma (GBM) having a
median survival of 15 months and five-year survival of less than 10 percent (Stupp et al., 2009), despite surgery,
chemotherapy (temozolomide), and radiation. While each of these approaches provides an overall survival
benefit of a few months, they do not offer a longer-term survival benefit or cure, even in combination. Thus, new
therapy approaches are sorely needed. To rationally develop therapies, it is critical that we have better
experimental systems for both fundamental and preclinical investigations that faithfully recapitulate key features
of the human disease while bringing the full power of state-of-the-art engineering approaches to bear including
modeling and simulation. In unpublished work, we have found that the Sleeping Beauty (SB) transposase system
we developed can be used to produce two major GBM, proneural (PN) and mesenchymal (MES), in immune-
competent wild-type mice using known human oncogenic drivers of glioblastoma, and that individual cancer cells
can be tracked in live tumors via multichannel fluorescence imaging. We hypothesize that mechanical forces
mediate a key targetable difference between PN and MES subtypes, and that the immune cold/hot signatures of
PN and MES subtypes represents a second key targetable difference between subtypes. To test these
hypotheses, we will measure cellular force and signaling dynamics of cancer cells and T cells in live GBM tumors
(Aim 1) and Measure immune cell dynamics in live GBM tumors (Aim 2). In particular we will measure cell traction
forces, kinase and GEF signaling, and extracellular matrix architecture in live tumors and brain tissue. In addition,
we will track antitumoral T cells, and protumoral microglia and bone marrow-derived macrophages, and their
correlations with each other and GBM cells, in the SB mouse models of PN and MES. These experiments will
be used to parameterize the Cell Migration Simulator (CMS) and Brownian Dynamics Tumor Simulator (BDTS)
to create predictive models that are GBM subtype-specific. In most cases, these measurements will be the first
of their kind in live GBM tumors, and will inform cell and tumor scale biophysical models. In so doing, RTB2 will
be providing a state-of-the-art integrated experimental-computational testbed for development of imaging
modalities in the TECH unit.

## Key facts

- **NIH application ID:** 10782993
- **Project number:** 5U54CA268069-03
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** David J. Odde
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $331,163
- **Award type:** 5
- **Project period:** 2021-12-09 → 2026-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10782993

## Citation

> US National Institutes of Health, RePORTER application 10782993, Research Testbed 2 (5U54CA268069-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10782993. Licensed CC0.

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