Radiogenomics, the integration of genomic data with radiation response, is emerging as a transformative approach for personalized radiotherapy. By identifying genetic biomarkers that predict tumor sensitivity to radiation, radiogenomics enables tailored treatment strategies to maximize efficacy and minimize toxicity. Recent studies highlight the role of key genes, such as ataxia-telangiectasia mutated (ATM), BRCA1/2, RAD51, CHEK1, and HIF-1α, in modulating radiation response through DNA repair, cell cycle regulation, hypoxia adaptation, and immune modulation. For instance, mutations in DNA repair genes like ATM and BRCA1/2 can impair the ability to fix radiation-induced double-strand breaks, rendering tumors more susceptible to radiation when combined with targeted therapies like PARP inhibitors. Similarly, hypoxia-related genes such as HIF-1α and CA9 promote tumor survival under low oxygen, contributing to radioresistance. Advances in next-generation sequencing and machine learning have refined radiogenomics, allowing for multi-omics integration to predict treatment outcomes. Immune-related biomarkers (PD-L1, CTLA4) guide radiotherapy-immunotherapy combinations, leveraging the abscopal effect to enhance systemic responses. Additionally, TP53 and MRE11 influence tumor sensitivity by regulating apoptosis and DNA damage response pathways. Despite its potential, radiogenomics faces challenges, including tumor heterogeneity, limited large-scale validation, and ethical concerns regarding genetic data usage. Addressing these barriers through interdisciplinary research and regulatory oversight is essential for fully integrating radiogenomics into clinical practice, ultimately improving patient outcomes.