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A human ex vivo model of radiation-induced skin injury recapitulates p53-driven profibrotic response to 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
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
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Research Article Dermatology Genetics Inflammation

A human ex vivo model of radiation-induced skin injury recapitulates p53-driven profibrotic response to radiotherapy

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Abstract

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.

Authors

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

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Figure 2

p53-mediated DNA damage response in irradiated ex vivo skin.

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p53-mediated DNA damage response in irradiated ex vivo skin.
(A) IPA of ...
(A) IPA of predicted upstream regulators and biological pathways associated with DNA damage responses across days 1, 2, 5, and 7 after irradiation. The first heatmap is colored by IPA z score (predicted activation state); the second shows Benjamini-Hochberg–corrected –log10 P values (e.g., 1.3 corresponds to P ≤ 0.05). Differentially expressed genes were filtered for protein-coding, P ≤ 0.05, and log2 fold-change ≥ ±0.5. z score heatmap rows were clustered by decreasing row average, with P value heatmap rows ordered to match. (B) Heatmap of TP53-regulated genes from RNA-seq data, showing row-scaled log2-transformed counts per million (CPM) values. Red indicates increased expression; blue indicates decreased expression. Columns represent individual samples labeled by donor and time point (e.g., DonorA_D1, DonorB_D7). Annotation bars indicate condition above the heatmap (pink = 3.5 Gy, black = control). (C) IPA-annotated “p53 signaling pathway” overlaid with RNA-seq gene expression changes on day 2 after irradiation. Genes are colored by predicted activation state (orange = activated, blue = inhibited). (D) qPCR of selected p53 target genes in human ex vivo skin on days 0, 2, and 7 after radiation of 0 Gy (black, n = 6), 3.5 Gy (pink, n = 6), or 6 Gy (teal, n = 3–4). Data were analyzed using the ΔΔCt method, normalized to GAPDH, and presented as fold-change relative to matched 0 Gy controls for each donor and time point; mean ± SD. Statistical significance was assessed using a mixed-effects model with Tukey’s test for multiple comparisons. Asterisks indicate statistical significance (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). All heatmaps were generated in RStudio using the pheatmap package.

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