# Mammalian models for integrated metabolic and molecular profiling of malignant glioma

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $554,109

## Abstract

PROJECT SUMMARY/ABSTRACT
Translational cancer research requires robust preclinical models to most effectively investigate the underlying
biology of disease and develop new therapeutics. While all models are imperfect, it is essential to understand
the degree by which each model system (e.g., cell culture, xenograft) recapitulates specific molecular and
functional characteristics of human tumors. This may be particularly relevant for studying altered metabolism, a
hallmark of cancer, as even subtle changes to the environment can greatly impact the metabolic phenotype of a
tumor. Moreover, as cancer metabolism is tightly regulated by oncogenic signaling, the diversity of molecular
alterations within a given malignancy may elicit unique metabolic characteristics; which, may greatly influence
metabolic pathway dependencies for tumor proliferation and growth. To best determine the fidelity of preclinical
models in preserving the metabolic features of human cancer, this requires cross-comparing matched patient
tissue and preclinical models across tumors with various genetic alterations. However, such a comprehensive
investigation has yet to be undertaken. This proposal will perform an integrated metabolic and molecular
characterization of matched human tumors, direct-from-patient orthotopic xenografts (GliomaPDOX), and cell
lines from patients with glioblastoma (GBM) – one of the most lethal human malignancies that also reside within
the unique brain metabolic milieu. In Aim 1, stable isotope-labeled metabolic tracing and liquid chromatography-
mass spectrometry (LC-MS) will be used to cross-compare the metabolic phenotypes of prospectively matched
GBM patient tumors, GliomaPDOX, and cell lines to determine the metabolic characteristics that are preserved
and/or lost from patient to preclinical model. Aim 2 proposes to determine, in genetically diverse preclinical
GliomaPDOX models, whether specific metabolic phenotypes align with distinct molecular signatures. Finally, in
Aim 3, in vivo genetic knockdown experiments will be performed to assess whether measured metabolic
phenotypes represent targetable dependencies for GliomaPDOX growth, invasion, and survival. Collectively, the
studies proposed in this application will provide critical insight into the translatability of preclinical GBM models
for studying tumor metabolism; which, may ultimately have important implications for developing new
therapeutics against metabolic dependencies in GBM, and potentially, other malignancies.

## Key facts

- **NIH application ID:** 10165664
- **Project number:** 5R01CA227089-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** THOMAS G GRAEBER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $554,109
- **Award type:** 5
- **Project period:** 2018-06-06 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10165664

## Citation

> US National Institutes of Health, RePORTER application 10165664, Mammalian models for integrated metabolic and molecular profiling of malignant glioma (5R01CA227089-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10165664. Licensed CC0.

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