The theme of radiogenomics and personalized therapy encompasses a range of studies aimed at improving treatment outcomes through the integration of genomic data and personalized therapeutic strategies. One significant study, ATALANTE-1, evaluated the efficacy of the cancer vaccine OSE2101 compared to standard chemotherapy in patients with advanced non-small-cell lung cancer (NSCLC) who had developed resistance to immunotherapy. This randomized controlled trial demonstrated that OSE2101 could offer a promising alternative for patients who have limited options due to primary or secondary resistance to immune checkpoint inhibitors (ref: Besse doi.org/10.1016/j.annonc.2023.07.006/). Another pivotal study developed a supervised risk predictor for breast cancer based on intrinsic subtypes, utilizing a 50-gene model to enhance prognostic accuracy and predict chemotherapy responses in a cohort of 761 patients (ref: Parker doi.org/10.1200/JCO.22.02511/). Furthermore, the INSIGhT trial introduced a phase II platform trial for glioblastoma, employing Bayesian adaptive randomization to identify effective therapies based on genomic profiling, showcasing the potential of adaptive trial designs in personalized medicine (ref: Rahman doi.org/10.1200/JCO.23.00493/). The combination of cytotoxic and immune-stimulatory gene therapy for high-grade gliomas also showed safety and feasibility, indicating a need for further exploration in larger trials (ref: Umemura doi.org/10.1016/S1470-2045(23)00347-9/). Lastly, the Neo-AEGIS trial compared trimodality therapy to perioperative chemotherapy in esophageal adenocarcinoma, revealing comparable overall survival rates, thus contributing to the ongoing debate about optimal treatment strategies in this challenging cancer type (ref: Reynolds doi.org/10.1016/S2468-1253(23)00243-1/).