# Pre-clinical testing of low intensity ultrasound as novel strategy to prevent paclitaxel-induced hair follicle damage in a humanized mouse model of chemotherapy-induced alopecia

> **NIH NIH R21** · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · 2023 · $394,687

## Abstract

PROJECT SUMMARY
 Taxanes like paclitaxel (PTX) are highly effective anti-microtubule agents frequently used in cancer
therapy, but they also cause major dose-limiting skin toxicity. The most dreaded of these is hair loss, which can
even be permanent. PTX-induced alopecia (PIA) severely impacts patients’ quality of life, and may lead to
refusal of life-saving chemotherapy. While scalp hair loss may be reduced by scalp cooling, this technology is
not yet widely available, cannot be applied to eyebrows, eyelashes and facial hair, and is of unpredictable
benefit. Therefore, prevention of this acute and chronic cancer-related morbidity will not only reduce distress,
anxiety, and depression associated with PIA, but likely also improve medication adherence.
 To this end, our project aims to generate proof-of-principle for the innovative strategy to protect hair
follicles (HFs) from alopecia by applying low intensity ultrasound (LIUS), a much-used and widely available
medical technology with an excellent safety profile. We have demonstrated that PTX stabilizes microtubules in
highly proliferative hair matrix keratinocytes, thus inducing their apoptosis and causing hair loss. In addition,
PTX also induces major HF stem cell damage, which can obliterate the HF’s capacity to regenerate. We have
also discovered that a brief exposure to LIUS can effectively neutralize the cytotoxic effects of PTX on cultured
cells by disrupting PTX-induced rigid microtubule bundles and thus prevent cell death. Most importantly, we
have generated preliminary evidence that LIUS also protects organ-cultured human scalp HFs and their
epithelial stem cells ex vivo as well as mouse HFs in vivo from PTX toxicity. Finally, we have established a
humanized mouse model for studying PIA by treating human scalp skin xenografts on SCID/beige mice with
PTX. This enables us, for the first time, to study candidate PTX-protective interventions under in vivo
conditions that optimally mimic the clinical reality of human PIA.
 As a critical step towards introducing this PIA prevention strategy into the clinic, we propose to test
preclinically whether LIUS is also PIA-protective in vivo, using our humanized PIA mouse model. Specifically,
we will determine how LIUS impacts on the microtubule network, function, and survival of human hair matrix
keratinocytes and HF stem cells under acute and repetitive PTX therapy. These studies will reveal whether
LIUS provides protection against acute and chronic damage by PTX to human HFs in vivo. The expected
results will guide the subsequent design of a clinical trial that probes the efficacy of LIUS in clinical PIA
prevention during ovarian cancer management. If successful, this innovative, drug-free, easily translatable and
widely available, economical, and very well-tolerated PIA prevention strategy will greatly improve the quality of
life of numerous taxane-treated cancer patients by liberating them from a major skin toxicity of oncological
therapy and will...

## Key facts

- **NIH application ID:** 10722518
- **Project number:** 1R21CA277418-01A1
- **Recipient organization:** UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
- **Principal Investigator:** Ralf Paus
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $394,687
- **Award type:** 1
- **Project period:** 2023-08-23 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10722518

## Citation

> US National Institutes of Health, RePORTER application 10722518, Pre-clinical testing of low intensity ultrasound as novel strategy to prevent paclitaxel-induced hair follicle damage in a humanized mouse model of chemotherapy-induced alopecia (1R21CA277418-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10722518. Licensed CC0.

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