Résumé
Testing individual radiosensitivity (RS) is crucial for personalized radiation oncology; however, its clinical implementation faces challenges due to biomarker variability and the absence of consensus. This review synthesizes recent advancements in RS prediction, emphasizing their translational potential and clinical applicability. A narrative review was conducted for the period 1980–2025 using PubMed/MEDLINE and radiobiology journals. Key themes included genetic markers (e.g., ATM/TGFB1 SNPs), functional assays (RILA, γ-H2AX foci), senescence biomarkers (p16/SASP), and omics technologies. The clinical validation status and limitations of these approaches were critically assessed. The Radiation-Induced Lymphocyte Apoptosis (RILA) assay demonstrates a robust correlation with late toxicity (multicenter AUC = 0.72 for breast fibrosis), while fibroblast-based assays (SF2, ATM translocation) show tissue-specific predictive value. Senescence markers (e.g., Th17/Treg ratio) and omics signatures (12-gene panel for head and neck squamous cell carcinoma) offer mechanistic insights but require standardization. The integration of machine learning and the development of senolytic therapies (e.g., dasatinib/quercetin) represent emerging frontiers in this field. RS prediction is transitioning from research to clinical utility, with RILA as the most validated assay. Future efforts must prioritize multicenter validation, cost-effective omics platforms, and biomarker-guided adaptive trials to optimize therapeutic ratios.
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•RILA assay demonstrates clinical validity for predicting late radiotoxicity, offering a practical 72-hour blood test to personalize treatment.•Radiation-induced senescence biomarkers and omics signatures reveal novel therapeutic targets, showing promise in mitigating toxicity.•A standardized framework combining functional assays, AI-based omics, and senolytic monitoring to link research and practice.