Cutaneous radiation injury is an unintended consequence of radiotherapy for many common cancers and can progress to debilitating radiation-induced skin fibrosis (RISF). Existing radiation injury models do not fully capture the skin toxicities observed in patients, contributing to the lack of efficacious therapies to mitigate RISF. To address this, we developed an ex vivo human skin model that recapitulates the temporal radiation injury and RISF response. Human skin explants (n = 12) subjected to ionizing radiation demonstrated DNA double-stranded breaks and robust p53-driven transcriptional programming of cell cycle arrest, apoptosis, and senescence compared with nonirradiated controls. Irradiated skin also exhibited induction of pro-inflammatory cytokines, epithelial-mesenchymal transition, profibrotic TGF-β1–mediated signaling, and thickened collagen over time. P53 regulators murine double minute 2 (MDM2) and miR-34a were induced after irradiation and may be leveraged to modulate injury response. Notably, RNA-sequencing of postradiotherapy breast skin from patients who had undergone mastectomy showed similar p53, inflammatory, and TGF-β1 signatures as the ex vivo model, supporting its translational relevance. Together, this model provides a platform for identifying biomarkers and testing therapies to prevent or mitigate cutaneous radiation toxicities. Targeting the dynamic p53-driven profibrotic radiation response represents a potentially new therapeutic avenue to improve quality of life for patients after radiotherapy.
Caroline Dodson, Sophie M. Bilik, Gabrielle DiBartolomeo, Hannah Pachalis, Lindsey G. Siegfried, Jordan A.K. Johnson, Seth R. Thaller, Irena Pastar, Marjana Tomic-Canic, Anthony J. Griswold, Rivka C. Stone
Usage data is cumulative from March 2026 through July 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 1,073 | 0 |
| 344 | 0 | |
| Figure | 6 | 0 |
| Supplemental data | 190 | 0 |
| Citation downloads | 212 | 0 |
| Totals | 1,825 | 0 |
| Total Views | 1,825 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.