# Metabolic Control of Hair Follicle Stem Cell Homeostasis and Tumorigenesis

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $421,908

## Abstract

PROJECT SUMMARY/ABSTRACT
The current project builds on our previous efforts to define and characterize cancer cells of origin within the
epidermis. We demonstrated that hair follicle stem cells are cells of origin for squamous cell carcinoma, and
that the inherent quiescence of these cells acts as a tumor suppressor mechanism. The current proposal
seeks to understand the role metabolism plays in both maintaining HFSCs, and also in their ability to initiate
tumorigenesis. Our preliminary data suggests that HFSCs possess a unique mode of metabolism, and we
seek to understand if this metabolic state is necessary to maintain these cells as quiescent, multipotent stem
cells. We will extend our characterization of HFSCs to include metabolomics approaches and determine
whether alteration of metabolic pathways disrupts their self-renewal or differentiation. Furthermore, with our
inducible tumor initiation model, we will be able to characterize the full extent of any metabolic transitions that
occur in vivo for the first time. We expect that these experiments will uncover novel mechanisms that regulate
HFSC biology, and perhaps even point towards new targeted therapeutics for HFSC initiated tumors.

## Key facts

- **NIH application ID:** 9883715
- **Project number:** 5R01AR070245-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Heather Christofk
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $421,908
- **Award type:** 5
- **Project period:** 2018-03-12 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9883715

## Citation

> US National Institutes of Health, RePORTER application 9883715, Metabolic Control of Hair Follicle Stem Cell Homeostasis and Tumorigenesis (5R01AR070245-03). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/9883715. Licensed CC0.

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