# Dissecting the cellular hierarchies of malignant gliomas by single-cell functional genomics

> **NIH NIH R37** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $505,201

## Abstract

Abstract
High-grade gliomas are a leading cause of cancer-related death in adults and children. They are highly
heterogeneous diseases in which both inter- and intra-tumoral heterogeneity contribute to disease
progression and therapeutic failure. In HGG, defined cellular states with key phenotypic
characteristics are selected for during tumorigenesis, drive tumor evolution, and underlie
resistance to therapy and invasion. In particular, HGG are thought to be driven by glioma stem cells
(GSC), subpopulations of cells recapitulating aspects of neural development that have the preferential
capacity to self-renew and to generate differentiated cancer cells. Traditional methodologies to identify
GSC rely on functional assays with important caveats and thus do not allow a comprehensive
characterization of cellular states in human patients. Additionally, while models of GSC and HGG are
extensively used for research, very little is known about their capacity to comprehensively mirror the
spectrum of cellular states present in patient samples; due to these limitations, vulnerabilities identified
in models frequently do not translate to clinical settings. Accordingly, we propose that the range of
cellular states that drive HGG should first be defined directly from patient samples, at single cell
resolution, and subsequently be functionally tested in animal and cell-based models. More
specifically, we will leverage single-cell RNA-sequencing and a comprehensive systems biology
approach in order to (I) identify tumor subpopulations unbiasedly across different genetic clones in
human HGG and in matched models of disease, at single-cell resolution; (II) functionally test the
capacity of these subpopulations to initiate tumors and to re-generate the diversity of states present in
patients; (III) identify faithful cell models that can recapitulate defined cellular states observed in patients
and utilize them to experimentally identify regulators with potential utility in clinical settings. Successful
completion of the research will fill a fundamental and large gap of knowledge in understanding
brain cancer in patients and in models and will provide novel opportunities to target key cellular
states that are driving these incurable malignancies. Furthermore, the proposed approach could be
extended to other malignancies, and will provide a proof-of-concept for uncovering subpopulations that
drive tumor growth directly from patient samples, and subsequently identifying regulators with potential
clinical relevance.

## Key facts

- **NIH application ID:** 9864798
- **Project number:** 1R37CA245523-01
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Mario Luca Suva
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $505,201
- **Award type:** 1
- **Project period:** 2020-03-01 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9864798

## Citation

> US National Institutes of Health, RePORTER application 9864798, Dissecting the cellular hierarchies of malignant gliomas by single-cell functional genomics (1R37CA245523-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9864798. Licensed CC0.

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