# Targeting Glutamine Uptake via ASCT2 Inhibition in MYCN-amplified Neuroblastomas

> **NIH NIH P20** · UNIVERSITY OF KENTUCKY · 2024 · $311,206

## Abstract

Neuroblastoma (NB) is the most common extracranial solid tumor in children. MYCN-amplification is present in ~25% of NBs and nearly half of all high-risk NBs. N-MYC is a proto-oncogene that drives cancer cell growth, angiogenesis, and metabolism. Aberrant glutamine metabolism is a hallmark of MYC-driven cancers. N-MYC enhances expression of the glutamine transporter, ASCT2. ASCT2 has been shown to be critical for MYCN-amplified NB cell survival in vitro and in subcutaneous xenograft formation in vivo. Our central hypothesis is that aberrant glutamine uptake via ASCT2 is critical for MYCN-amplified NB primary tumor growth and metastasis. We will define the critical role of ASCT2 in NB utilizing CRISPR-Cas9 knockout and V-9302, a small molecule ASCT2 inhibitor, in 3-D organoid and patient-derived orthotopic xenograft (PDOX) models of MYCN-amplified NB. Stable-isotope resolved metabolomics will be used to define aberrant metabolic pathways activated to sustain NB survival in the presence of ASCT2 blockade. We will also seek to define metabolic vulnerabilities uncovered by ASCT2 inhibition utilizing an unbiased CRISPR-Cas9 lineage dropout screen to assess for dual synthetic lethality in MYCN-amplified NB cells.

## Key facts

- **NIH application ID:** 10757437
- **Project number:** 5P20GM121327-08
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** Eric James Rellinger
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $311,206
- **Award type:** 5
- **Project period:** 2017-03-01 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10757437

## Citation

> US National Institutes of Health, RePORTER application 10757437, Targeting Glutamine Uptake via ASCT2 Inhibition in MYCN-amplified Neuroblastomas (5P20GM121327-08). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10757437. Licensed CC0.

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