High-throughput strategy for targeting MDM2 in uveal melanoma to reverse radiation therapy resistance

Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy combining machine learning models with high-throughput screening platforms was employed to identify novel small-molecule inhibitors targeting MDM2, with the aim of overcoming this intrinsic resistance. Transcriptome sequencing and machine learning analysis identified MDM2 as a critical gene associated with UM radiotherapy resistance. Integration of single-cell RNA sequencing data revealed key cells contributing to this resistance. In vitro experiments demonstrated that the MDM2 inhibitor SAR405838 effectively increased radiosensitivity in resistant UM cells by modulating p53 activation, suppressing cell migration and invasion, and inducing DNA damage and apoptosis. This novel approach offers a promising therapeutic strategy for combating UM resistance to radiation therapy.