# Adapting Functional Precision Oncology for pediatric brain cancer

> **NIH NIH U24** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $152,418

## Abstract

ABSTRACT
Cancers are typically composed of heterogeneous populations of tumors cells characterized by mutations that
distinguish each cell subpopulation from one another. The parent grant leverages DNA sequencing and a suite
of important new analytical algorithms and visualization tools to identify mutations in cancer patients and track
the evolution of a patient’s tumor over the course of treatment. The tools we have developed, or are in the
process of developing, form the foundation of a functional precision oncology approach we are implementing at
the University of Utah with a combination of set-aside funding from the parent project, and institutional funding.
The current Supplemental Request will adapt the tools funded by the parent project for effective use in pediatric
cancers. The main objective of this Supplemental Proposal is to adapt our functional precision oncology
approach to inform treatment selection in children with brain tumors, a patient cohort that experiences extremely
dire prognoses in which rational treatment choice is difficult without precision guidance. There are compelling
reasons to believe, however, that such adaptation will require algorithmic modifications. This is because key
aspects of our approach rely on genomic mutations in the tumor, but previous studies show that pediatric tumors
have a substantially lower mutation load than adult cancers. Therefore it is necessary to expand our functional
approach in pediatric cases, and adapt them to lower mutation loads in pediatric tumors. To accomplish such
adaptation, we will, first, perform functional drug screening and genomic/transcriptomic characterization in two
pediatric brain cancer index patients, so we have appropriate test cases drivin our tool development and testing.
We will then, second, analyze the pediatric brain tumor index patient datasets, and adapt our functional precision
informatics methods for use in pediatric brain tumors with expected lower genomic mutation loads. We foresee
two specific areas of development: because of the substantially lower number of mutations in the pediatric cases,
we will integrate the ability to simultaneously analyze somatic copy number variation (CNV) mutations, together
with somatic point mutations to (1) reconstruct the genomic subclones that make up the tumor; and (2) to carry
out cell assignment to the genomically defined sublones from single-cell RNA sequencing data used to study
tumor subclone-specific gene expression behavior. We have already shown that CNVs can be used both for
tumor subclone reconstruction and cell assignment, and anticipate that by integrating CNV and point mutation-
based analyses in a single tool will allow functional precision analysis of pediatric cancer patients at, or close to,
the level achievable for adult patients.
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## Key facts

- **NIH application ID:** 10227337
- **Project number:** 3U24CA209999-05S1
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Gabor T Marth
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $152,418
- **Award type:** 3
- **Project period:** 2016-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10227337

## Citation

> US National Institutes of Health, RePORTER application 10227337, Adapting Functional Precision Oncology for pediatric brain cancer (3U24CA209999-05S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10227337. Licensed CC0.

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