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Detalle de: Deciphering the Dynamic Molecular Program of Radiation-Induced Endothelial Senescence

Title Deciphering the Dynamic Molecular Program of Radiation-Induced Endothelial Senescence
Abstract

Radiation-induced cellular senescence is a double-edged sword, acting as both a tumor suppression process limiting tumor proliferation, and a crucial process contributing to normal tissue injury. Endothelial cells play a role in normal tissue injury after radiation therapy. Recently, a study observed an accumulation of senescent endothelial cells (ECs) around radiation-induced lung focal lesions following stereotactic radiation injury in mice. However, the effect of radiation on EC senescence remains unclear because it depends on dose and fractionation, and because the senescent phenotype is heterogeneous and dynamic.

Using a systems biology approach in vitro, we deciphered the dynamic senescence-associated transcriptional program induced by irradiation. Flow cytometry and single-cell RNA sequencing experiments revealed the heterogeneous senescent status of irradiated ECs and allowed to deciphered the molecular program involved in this status. We identified the Interleukin-1 signalling pathway as a key player in the radiation-induced premature senescence of ECs, as well as the endothelial-to-mesenchymal transition process, which shares strong hallmarks of senescence. Our work provides crucial information on the dynamics of the radiation-induced premature senescence process, the effect of the radiation dose, as well as the molecular program involved in the heterogeneous senescent status of ECs.

    Apa Reference Benadjaoud, M. A., Soysouvanh, F., Tarlet, G., Paget, V., Buard, V., Santos de Andrade, H., … Milliat, F. (2022). Deciphering the dynamic molecular program of radiation-induced endothelial senescence. International Journal of Radiation Oncology, Biology, Physics, 112(4), 975–985. doi:10.1016/j.ijrobp.2021.11.019
    Doi 10.1016/j.ijrobp.2021.11.019
    Publication Date Mar 2022
    Publication Type Article
    Researcher Ian Morilla
    Ontology Transcriptomics, RNA Sequencing (RNA-seq), Systems Biology, Single-cell omics
    Research Groups Machine Learning in Multi-Omics (MLiMO)
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